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Feb-2025
论文阅读
[Feb-20] SigLIP 2: Multilingual Vision-Language Encoders with Improved Semantic Understanding, Localization, and Dense Features
Jan-2025
论文阅读
[Jan-13] The GAN is dead; long live the GAN! A Modern GAN Baseline
Nov-2024
论文阅读
[Nov-25] DINO-X: A Unified Vision Model for Open-World Object Detection and Understanding
论文阅读
[Nov-22] DODA: Diffusion for Object-detection Domain Adaptation in Agriculture
论文阅读
[Nov-15] CLIBD: Bridging Vision and Genomics for Biodiversity Monitoring at Scale
论文阅读
[Nov-3] Adapting the Segment Anything Model for Plant Recognition and Automated Phenotypic Parameter Measurement
论文阅读
[Nov-2] Adapting Vision Foundation Models for Plant Phenotyping
深度学习
[Nov-1] 表型图像分析(Phenotypic Image Analysis)
Oct-2024
游记
[Oct-21] （浙江篇）安吉：绿水青山就是金山银山
论文阅读
[Oct-20] Pan-Mamba: Effective pan-sharpening with State Space Model
论文阅读
[Oct-19] PanFlowNet: A Flow-Based Deep Network for Pan-sharpening
论文阅读
[Oct-18] Revisiting Spatial-Frequency Information Integration from a Hierarchical Perspective for Panchromatic and Multi-Spectral Image Fusion
论文阅读
[Oct-17] Deep Gradient Projection Networks for Pan-sharpening
论文阅读
[Oct-16] Mutual Information-driven Pan-sharpening
论文阅读
[Oct-15] Spatial-Frequency Domain Information Integration for Pan-Sharpening
论文阅读
[Oct-14] PanFormer: a Transformer Based Model for Pan-sharpening
论文阅读
[Oct-13] Pan-Sharpening with Customized Transformer and Invertible Neural Network
论文阅读
[Oct-12] Super-Resolution-Guided Progressive Pansharpening based on a Deep Convolutional Neural Network
论文阅读
[Oct-11] A Multi-Scale and Multi-Depth Convolutional Neural Network for Remote Sensing Imagery Pan-Sharpening
论文阅读
[Oct-10] PanNet: A Deep Network Architecture for Pan-Sharpening
论文阅读
[Oct-9] Pansharpening by Convolutional Neural Networks
深度学习
[Oct-8] 全色锐化(Panchromatic Sharpening)
游记
[Oct-3] （日本篇）富士：谁能凭爱意要富士山私有
游记
[Oct-2] （日本篇）镰仓：幕府！江岛？大灌篮！
游记
[Oct-1] （日本篇）东京：东京之旅一早比一世遥远
Aug-2024
数学
[Aug-30] 欧拉路径(Euler Path)与de Bruijn图
论文阅读
[Aug-29] A universal SNP and small-indel variant caller using deep neural networks
Jul-2024
论文阅读
[Jul-16] LoRA-GA: Low-Rank Adaptation with Gradient Approximation
随笔
[Jul-14] 宝可梦北京大师赛将出现最强的口袋迷ag！
论文阅读
[Jul-9] On the Parameterization and Initialization of Diagonal State Space Models
论文阅读
[Jul-8] Simplified State Space Layers for Sequence Modeling
论文阅读
[Jul-7] Diagonal State Spaces are as Effective as Structured State Spaces
论文阅读
[Jul-5] Combining Recurrent, Convolutional, and Continuous-time Models with Linear State-Space Layers
论文阅读
[Jul-4] Legendre Memory Units: Continuous-Time Representation in Recurrent Neural Networks
论文阅读
[Jul-3] Efficiently Modeling Long Sequences with Structured State Spaces
论文阅读
[Jul-2] HiPPO: Recurrent Memory with Optimal Polynomial Projections
深度学习
[Jul-1] 状态空间模型(State Space Model)
Jun-2024
随笔
[Jun-16] 二十四年磨一剑：毕业小记
游记
[Jun-9] （河北篇）唐山：唐山很“唐”
论文阅读
[Jun-7] Human Posture Reconstruction for Through-the-Wall Radar Imaging Using Convolutional Neural Networks
论文阅读
[Jun-6] Recovering Human Pose and Shape From Through-the-Wall Radar Images
论文阅读
[Jun-5] Unsupervised Human Contour Extraction From Through-Wall Radar Images Using Dual UNet
论文阅读
[Jun-4] Through-Wall Human Pose Reconstruction Based on Cross-Modal Learning and Self-Supervised Learning
论文阅读
[Jun-3] Through-Wall Human Pose Estimation by Mutual Information Maximizing Deeply Supervised Nets
论文阅读
[Jun-2] RadarFormer: End-to-End Human Perception With Through-Wall Radar and Transformers
深度学习
[Jun-1] 射频人体感知(RF-based Human Perception)
May-2024
论文阅读
[May-23] YOLOv10: Real-Time End-to-End Object Detection
论文阅读
[May-20] Learning Spatial Similarity Distribution for Few-shot Object Counting
数学
[May-7] 样条曲线(Spline Curve)
论文阅读
[May-6] KAN: Kolmogorov-Arnold Networks
游记
[May-2] （内蒙古篇）乌兰察布：红色的山口
游记
[May-1] （内蒙古篇）呼和浩特：青色的城
Apr-2024
论文阅读
[Apr-25] DAVE -- A Detect-and-Verify Paradigm for Low-Shot Counting
论文阅读
[Apr-5] Score identity Distillation: Exponentially Fast Distillation of Pretrained Diffusion Models for One-Step Generation
Mar-2024
论文阅读
[Mar-20] DetDiffusion: Synergizing Generative and Perceptive Models for Enhanced Data Generation and Perception
论文阅读
[Mar-19] GeoDiffusion: Text-Prompted Geometric Control for Object Detection Data Generation
论文阅读
[Mar-8] OmniCount: Multi-label Object Counting with Semantic-Geometric Priors
论文阅读
[Mar-7] InstanceDiffusion: Instance-level Control for Image Generation
论文阅读
[Mar-6] LayoutDiffuse: Adapting Foundational Diffusion Models for Layout-to-Image Generation
论文阅读
[Mar-5] Adding Conditional Control to Text-to-Image Diffusion Models
论文阅读
[Mar-4] ReCo: Region-Controlled Text-to-Image Generation
论文阅读
[Mar-3] LayoutDiffusion: Controllable Diffusion Model for Layout-to-image Generation
论文阅读
[Mar-2] GLIGEN: Open-Set Grounded Text-to-Image Generation
深度学习
[Mar-1] 布局引导图像生成(Layout-to-Image Generation)
Feb-2024
论文阅读
[Feb-29] Sigmoid Loss for Language Image Pre-Training
论文阅读
[Feb-28] VL-BEiT: Generative Vision-Language Pretraining
论文阅读
[Feb-21] YOLOv9: Learning What You Want to Learn Using Programmable Gradient Information
论文阅读
[Feb-19] LoRA+: Efficient Low Rank Adaptation of Large Models
论文阅读
[Feb-17] Video generation models as world simulators
论文阅读
[Feb-8] Enhancing Zero-shot Counting via Language-guided Exemplar Learning
游记
[Feb-3] （辽宁篇）沈阳：龙行龘龘，沈水之阳
Jan-2024
论文阅读
[Jan-31] Image as a Foreign Language: BEiT Pretraining for All Vision and Vision-Language Tasks
论文阅读
[Jan-30] Improving CLIP Training with Language Rewrites
论文阅读
[Jan-29] Scaling Up Visual and Vision-Language Representation Learning With Noisy Text Supervision
论文阅读
[Jan-28] Attentive Mask CLIP
论文阅读
[Jan-27] MaskCLIP: Masked Self-Distillation Advances Contrastive Language-Image Pretraining
论文阅读
[Jan-26] Scaling Language-Image Pre-training via Masking
论文阅读
[Jan-25] SLIP: Self-supervision meets Language-Image Pre-training
论文阅读
[Jan-24] Chinese CLIP: Contrastive Vision-Language Pretraining in Chinese
论文阅读
[Jan-23] BLIP-2: Bootstrapping Language-Image Pre-training with Frozen Image Encoders and Large Language Models
论文阅读
[Jan-22] BLIP: Bootstrapping Language-Image Pre-training for Unified Vision-Language Understanding and Generation
论文阅读
[Jan-21] GLIPv2: Unifying Localization and Vision-Language Understanding
游记
[Jan-20] （河北篇）保定：推开京畿之门
Python
[Jan-19] 微调 Grounding DINO 和 Label Studio 进行半自动化目标检测标注
论文阅读
[Jan-18] CoCa: Contrastive Captioners are Image-Text Foundation Models
论文阅读
[Jan-17] VinVL: Revisiting Visual Representations in Vision-Language Models
论文阅读
[Jan-16] SimVLM: Simple Visual Language Model Pretraining with Weak Supervision
论文阅读
[Jan-15] GIT: A Generative Image-to-text Transformer for Vision and Language
论文阅读
[Jan-14] VLMo: Unified Vision-Language Pre-Training with Mixture-of-Modality-Experts
论文阅读
[Jan-13] Align before Fuse: Vision and Language Representation Learning with Momentum Distillation
论文阅读
[Jan-12] ViLT: Vision-and-Language Transformer Without Convolution or Region Supervision
论文阅读
[Jan-11] Multimodal Few-Shot Learning with Frozen Language Models
论文阅读
[Jan-10] Unifying Vision-and-Language Tasks via Text Generation
论文阅读
[Jan-9] ImageBERT: Cross-modal Pre-training with Large-scale Weak-supervised Image-Text Data
随笔
[Jan-9] 浅评《回声》：衍生的衍生，难有回声
论文阅读
[Jan-8] Pixel-BERT: Aligning Image Pixels with Text by Deep Multi-Modal Transformers
论文阅读
[Jan-7] UNITER: UNiversal Image-TExt Representation Learning
论文阅读
[Jan-6] Oscar: Object-Semantics Aligned Pre-training for Vision-Language Tasks
论文阅读
[Jan-5] VL-BERT: Pre-training of Generic Visual-Linguistic Representations
论文阅读
[Jan-4] ViLBERT: Pretraining Task-Agnostic Visiolinguistic Representations for Vision-and-Language Tasks
论文阅读
[Jan-3] VisualBERT: A Simple and Performant Baseline for Vision and Language
论文阅读
[Jan-2] LXMERT: Learning Cross-Modality Encoder Representations from Transformers
深度学习
[Jan-1] 视觉-语言预训练(Vision-Language Pretraining)
Dec-2023
论文阅读
[Dec-27] VLCounter: Text-aware Visual Representation for Zero-Shot Object Counting
Nov-2023
随笔
[Nov-30] 浅评《洛基（第二季）》：自由意志与成为神的代价
随笔
[Nov-29] 浅评《惊奇队长2》：门槛更高，失望更快，彩蛋更强
论文阅读
[Nov-28] Semantic Generative Augmentations for Few-Shot Counting
论文阅读
[Nov-15] DetCLIPv2: Scalable Open-Vocabulary Object Detection Pre-training via Word-Region Alignment
论文阅读
[Nov-14] DetCLIP: Dictionary-Enriched Visual-Concept Paralleled Pre-training for Open-world Detection
论文阅读
[Nov-13] Learning Object-Language Alignments for Open-Vocabulary Object Detection
论文阅读
[Nov-12] RegionCLIP: Region-based Language-Image Pretraining
论文阅读
[Nov-11] Exploiting Unlabeled Data with Vision and Language Models for Object Detection
Python
[Nov-10] 目标检测数据集的分析
论文阅读
[Nov-9] Detecting Twenty-thousand Classes using Image-level Supervision
论文阅读
[Nov-8] Open Vocabulary Object Detection with Pseudo Bounding-Box Labels
论文阅读
[Nov-7] Open-vocabulary Object Detection via Vision and Language Knowledge Distillation
论文阅读
[Nov-6] Open-Vocabulary Object Detection Using Captions
论文阅读
[Nov-5] MDETR -- Modulated Detection for End-to-End Multi-Modal Understanding
论文阅读
[Nov-4] Towards Open-Set Object Detection and Discovery
论文阅读
[Nov-3] Grounded Language-Image Pre-training
论文阅读
[Nov-2] Grounding DINO: Marrying DINO with Grounded Pre-Training for Open-Set Object Detection
深度学习
[Nov-1] 开放集合目标检测(Open-Set Object Detection)
Sep-2023
论文阅读
[Sep-27] Finite Scalar Quantization: VQ-VAE Made Simple
论文阅读
[Sep-9] ABC Easy as 123: A Blind Counter for Exemplar-Free Multi-Class Class-agnostic Counting
Jul-2023
论文阅读
[Jul-31] Effective Whole-body Pose Estimation with Two-stages Distillation
游记
[Jul-23] （澳门篇）你可知妈港不是我的真名姓？
论文阅读
[Jul-14] MPDIoU: A Loss for Efficient and Accurate Bounding Box Regression
论文阅读
[Jul-4] SDXL: Improving Latent Diffusion Models for High-Resolution Image Synthesis
Jun-2023
论文阅读
[Jun-30] Open-world Text-specified Object Counting
论文阅读
[Jun-13] One-for-All: Generalized LoRA for Parameter-Efficient Fine-tuning
论文阅读
[Jun-7] Faster sorting algorithms discovered using deep reinforcement learning
May-2023
论文阅读
[May-28] Towards Partial Supervision for Generic Object Counting in Natural Scenes
论文阅读
[May-27] Object Counting and Instance Segmentation with Image-level Supervision
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[May-26] Class-aware Object Counting
论文阅读
[May-25] MoVie: Revisiting Modulated Convolutions for Visual Counting and Beyond
论文阅读
[May-24] Dilated-Scale-Aware Attention ConvNet For Multi-Class Object Counting
论文阅读
[May-23] QLoRA: Efficient Finetuning of Quantized LLMs
论文阅读
[May-22] Zero-shot Improvement of Object Counting with CLIP
论文阅读
[May-21] Teaching CLIP to Count to Ten
论文阅读
[May-20] Can SAM Count Anything? An Empirical Study on SAM Counting
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[May-19] Vicinal Counting Networks
论文阅读
[May-18] Class-agnostic Few-shot Object Counting
论文阅读
[May-17] GCNet: Probing Self-Similarity Learning for Generalized Counting Network
论文阅读
[May-16] Mimetic Initialization of Self-Attention Layers
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[May-15] Vision Transformer Off-the-Shelf: A Surprising Baseline for Few-Shot Class-Agnostic Counting
论文阅读
[May-14] Zero-shot Object Counting
论文阅读
[May-13] Scale-Prior Deformable Convolution for Exemplar-Guided Class-Agnostic Counting
论文阅读
[May-12] CLIP-Count: Towards Text-Guided Zero-Shot Object Counting
论文阅读
[May-11] A Low-Shot Object Counting Network With Iterative Prototype Adaptation
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[May-10] CounTR: Transformer-based Generalised Visual Counting
论文阅读
[May-9] Exemplar Free Class Agnostic Counting
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[May-8] Few-shot Object Counting and Detection
论文阅读
[May-7] Learning to Count Anything: Reference-less Class-agnostic Counting with Weak Supervision
论文阅读
[May-6] Represent, Compare, and Learn: A Similarity-Aware Framework for Class-Agnostic Counting
论文阅读
[May-5] Few-shot Object Counting with Similarity-Aware Feature Enhancement
论文阅读
[May-4] Object Counting: You Only Need to Look at One
论文阅读
[May-3] Learning To Count Everything
论文阅读
[May-2] Class-Agnostic Counting
深度学习
[May-1] 目标计数(Object Counting)
Apr-2023
数学
[Apr-13] 局部敏感哈希(Locality Sensitive Hashing)
论文阅读
[Apr-10] PCT: Point cloud transformer
论文阅读
[Apr-9] PointNet++: Deep Hierarchical Feature Learning on Point Sets in a Metric Space
论文阅读
[Apr-8] Dynamic Graph CNN for Learning on Point Clouds
论文阅读
[Apr-7] PointCNN: Convolution On X-Transformed Points
论文阅读
[Apr-6] Segment Anything
论文阅读
[Apr-5] PointNet: Deep Learning on Point Sets for 3D Classification and Segmentation
论文阅读
[Apr-4] OctNet: Learning Deep 3D Representations at High Resolutions
论文阅读
[Apr-3] VoxNet: A 3D Convolutional Neural Network for Real-Time Object Recognition
论文阅读
[Apr-2] Multi-view Convolutional Neural Networks for 3D Shape Recognition
深度学习
[Apr-1] 点云分类(Point Cloud Classification)
Mar-2023
论文阅读
[Mar-31] RTMPose: Real-Time Multi-Person Pose Estimation based on MMPose
数学
[Mar-25] 集函数的子模性(Submodularity)与Lovász延拓(Lovász Extension)
数学
[Mar-22] 二值图像的距离变换(Distance Transform)
论文阅读
[Mar-21] Human Pose as Compositional Tokens
论文阅读
[Mar-20] Self-Correctable and Adaptable Inference for Generalizable Human Pose Estimation
论文阅读
[Mar-18] Adaptive Budget Allocation for Parameter-Efficient Fine-Tuning
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[Mar-15] DeepMIM: Deep Supervision for Masked Image Modeling
论文阅读
[Mar-14] Masked Image Modeling with Local Multi-Scale Reconstruction
Feb-2023
论文阅读
[Feb-21] Symbolic Discovery of Optimization Algorithms
Python
[Feb-20] 使用einops实现张量操作
论文阅读
[Feb-18] Visual Prompt Tuning
论文阅读
[Feb-17] AdaMix: Mixture-of-Adaptations for Parameter-efficient Model Tuning
论文阅读
[Feb-16] AdaptFormer: Adapting Vision Transformers for Scalable Visual Recognition
论文阅读
[Feb-15] LST: Ladder Side-Tuning for Parameter and Memory Efficient Transfer Learning
论文阅读
[Feb-14] UniPELT: A Unified Framework for Parameter-Efficient Language Model Tuning
论文阅读
[Feb-13] Towards a Unified View of Parameter-Efficient Transfer Learning
论文阅读
[Feb-12] Parameter-Efficient Transfer Learning with Diff Pruning
论文阅读
[Feb-11] DensePose From WiFi
论文阅读
[Feb-10] LoRA: Low-Rank Adaptation of Large Language Models
论文阅读
[Feb-9] AdapterDrop: On the Efficiency of Adapters in Transformers
论文阅读
[Feb-8] AdapterFusion: Non-Destructive Task Composition for Transfer Learning
论文阅读
[Feb-7] P-Tuning v2: Prompt Tuning Can Be Comparable to Fine-tuning Universally Across Scales and Tasks
论文阅读
[Feb-6] GPT Understands, Too
论文阅读
[Feb-5] The Power of Scale for Parameter-Efficient Prompt Tuning
论文阅读
[Feb-4] Prefix-Tuning: Optimizing Continuous Prompts for Generation
论文阅读
[Feb-3] BitFit: Simple Parameter-efficient Fine-tuning for Transformer-based Masked Language-models
深度学习
[Feb-2] 大模型的参数高效微调(Parameter-Efficient Fine-Tuning)
论文阅读
[Feb-1] Parameter-Efficient Transfer Learning for NLP
Jan-2023
论文阅读
[Jan-31] Ultralytics YOLOv8
论文阅读
[Jan-25] Refiner: Refining Self-attention for Vision Transformers
论文阅读
[Jan-24] Improve Vision Transformers Training by Suppressing Over-smoothing
论文阅读
[Jan-23] Twins: Revisiting the Design of Spatial Attention in Vision Transformers
论文阅读
[Jan-22] All Tokens Matter: Token Labeling for Training Better Vision Transformers
论文阅读
[Jan-21] Incorporating Convolution Designs into Visual Transformers
论文阅读
[Jan-20] CvT: Introducing Convolutions to Vision Transformers
论文阅读
[Jan-19] Per-Pixel Classification is Not All You Need for Semantic Segmentation
论文阅读
[Jan-18] Pyramid Vision Transformer: A Versatile Backbone for Dense Prediction without Convolutions
论文阅读
[Jan-17] Segmenter: Transformer for Semantic Segmentation
论文阅读
[Jan-16] Rethinking Spatial Dimensions of Vision Transformers
论文阅读
[Jan-15] SegFormer: Simple and Efficient Design for Semantic Segmentation with Transformers
论文阅读
[Jan-14] TransUNet: Transformers Make Strong Encoders for Medical Image Segmentation
论文阅读
[Jan-13] Rethinking Semantic Segmentation from a Sequence-to-Sequence Perspective with Transformers
论文阅读
[Jan-12] CrossViT: Cross-Attention Multi-Scale Vision Transformer for Image Classification
论文阅读
[Jan-11] Do We Really Need Explicit Position Encodings for Vision Transformers?
论文阅读
[Jan-10] Visual Transformers: Token-based Image Representation and Processing for Computer Vision
论文阅读
[Jan-9] LeViT: a Vision Transformer in ConvNet’s Clothing for Faster Inference
论文阅读
[Jan-8] Escaping the Big Data Paradigm with Compact Transformers
论文阅读
[Jan-7] Tokens-to-Token ViT: Training Vision Transformers from Scratch on ImageNet
论文阅读
[Jan-6] Going deeper with Image Transformers
论文阅读
[Jan-5] ConvNeXt V2: Co-designing and Scaling ConvNets with Masked Autoencoders
论文阅读
[Jan-4] DeepViT: Towards Deeper Vision Transformer
论文阅读
[Jan-3] Training data-efficient image transformers & distillation through attention
论文阅读
[Jan-2] Better plain ViT baselines for ImageNet-1k
深度学习
[Jan-1] 视觉Transformer(Vision Transformer)
Dec-2022
论文阅读
[Dec-30] Position Prediction as an Effective Pretraining Strategy
机器学习
[Dec-29] 类别型特征提升(Categorical Boosting, CatBoost)
机器学习
[Dec-28] 轻量级梯度提升机(Light Gradient Boosting Machine, LightGBM)
机器学习
[Dec-27] 极限梯度提升(eXtreme Gradient Boosting, XGBoost)
论文阅读
[Dec-26] Pooling Revisited: Your Receptive Field is Suboptimal
论文阅读
[Dec-25] A ConvNet for the 2020s
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[Dec-24] Deformable Convolutional Networks
论文阅读
[Dec-23] Deformable ConvNets v2: More Deformable, Better Results
论文阅读
[Dec-22] CondConv: Conditionally Parameterized Convolutions for Efficient Inference
论文阅读
[Dec-21] Dynamic Convolution: Attention over Convolution Kernels
论文阅读
[Dec-20] DyNet: Dynamic Convolution for Accelerating Convolutional Neural Networks
论文阅读
[Dec-19] Omni-Dimensional Dynamic Convolution
论文阅读
[Dec-18] Drop an Octave: Reducing Spatial Redundancy in Convolutional Neural Networks with Octave Convolution
论文阅读
[Dec-17] Dynamic Region-Aware Convolution
论文阅读
[Dec-16] An Intriguing Failing of Convolutional Neural Networks and the CoordConv Solution
论文阅读
[Dec-15] Inception Convolution with Efficient Dilation Search
论文阅读
[Dec-9] Heatmap Distribution Matching for Human Pose Estimation
论文阅读
[Dec-8] AlphaPose: Whole-Body Regional Multi-Person Pose Estimation and Tracking in Real-Time
论文阅读
[Dec-7] RTMDet: An Empirical Study of Designing Real-Time Object Detectors
数学
[Dec-6] 积分概率度量(Integral Probability Metric)
论文阅读
[Dec-2] Amos: An Adam-style Optimizer with Adaptive Weight Decay towards Model-Oriented Scale
Nov-2022
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[Nov-30] Contrastive Learning Rivals Masked Image Modeling in Fine-tuning via Feature Distillation
论文阅读
[Nov-29] Parametric Instance Classification for Unsupervised Visual Feature Learning
论文阅读
[Nov-28] Self-Supervised Learning based on Heat Equation
论文阅读
[Nov-27] Revealing the Dark Secrets of Masked Image Modeling
论文阅读
[Nov-26] On Data Scaling in Masked Image Modeling
论文阅读
[Nov-25] ConvMAE: Masked Convolution Meets Masked Autoencoders
论文阅读
[Nov-24] SimMIM: A Simple Framework for Masked Image Modeling
论文阅读
[Nov-23] iBOT: Image BERT Pre-Training with Online Tokenizer
论文阅读
[Nov-22] BEiT: BERT Pre-Training of Image Transformers
论文阅读
[Nov-21] Discovering faster matrix multiplication algorithms with reinforcement learning
论文阅读
[Nov-20] Analyzing and Improving Representations with the Soft Nearest Neighbor Loss
论文阅读
[Nov-19] Circle Loss: A Unified Perspective of Pair Similarity Optimization
论文阅读
[Nov-18] Multi-Similarity Loss with General Pair Weighting for Deep Metric Learning
论文阅读
[Nov-17] Person re-identification by multi-channel parts-based CNN with improved triplet loss function
论文阅读
[Nov-16] In Defense of the Triplet Loss for Person Re-Identification
论文阅读
[Nov-15] Ranked List Loss for Deep Metric Learning
论文阅读
[Nov-14] ProxyNCA++: Revisiting and Revitalizing Proxy Neighborhood Component Analysis
论文阅读
[Nov-13] Proxy Anchor Loss for Deep Metric Learning
论文阅读
[Nov-12] Deep Metric Learning for Practical Person Re-Identification
论文阅读
[Nov-11] No Fuss Distance Metric Learning using Proxies
论文阅读
[Nov-10] Deep Metric Learning with Hierarchical Triplet Loss
论文阅读
[Nov-9] Deep Metric Learning via Facility Location
论文阅读
[Nov-8] Beyond triplet loss: a deep quadruplet network for person re-identification
论文阅读
[Nov-7] Deep Metric Learning with Angular Loss
论文阅读
[Nov-6] Metric Learning with Adaptive Density Discrimination
论文阅读
[Nov-5] Improved Deep Metric Learning with Multi-class N-pair Loss Objective
论文阅读
[Nov-4] Learning Deep Embeddings with Histogram Loss
论文阅读
[Nov-3] Deep Metric Learning via Lifted Structured Feature Embedding
论文阅读
[Nov-2] FaceNet: A Unified Embedding for Face Recognition and Clustering
深度学习
[Nov-1] 度量学习(Metric Learning)
Oct-2022
论文阅读
[Oct-31] Jigsaw Clustering for Unsupervised Visual Representation Learning
论文阅读
[Oct-30] Propagate Yourself: Exploring Pixel-Level Consistency for Unsupervised Visual Representation Learning
论文阅读
[Oct-29] Emerging Properties in Self-Supervised Vision Transformers
论文阅读
[Oct-28] Characterizing and Improving the Robustness of Self-Supervised Learning through Background Augmentations
论文阅读
[Oct-27] Evolving Losses for Unsupervised Video Representation Learning
论文阅读
[Oct-26] Exploring Simple Siamese Representation Learning
论文阅读
[Oct-25] CURL: Contrastive Unsupervised Representations for Reinforcement Learning
论文阅读
[Oct-24] Unsupervised Learning of Visual Features by Contrasting Cluster Assignments
论文阅读
[Oct-23] An Empirical Study of Training Self-Supervised Vision Transformers
论文阅读
[Oct-22] Improved Baselines with Momentum Contrastive Learning
论文阅读
[Oct-21] Momentum Contrast for Unsupervised Visual Representation Learning
论文阅读
[Oct-20] Contrastive Multiview Coding
论文阅读
[Oct-19] Unsupervised Feature Learning via Non-Parametric Instance-level Discrimination
论文阅读
[Oct-18] Unsupervised Embedding Learning via Invariant and Spreading Instance Feature
论文阅读
[Oct-17] Bootstrap your own latent: A new approach to self-supervised Learning
论文阅读
[Oct-16] Barlow Twins: Self-Supervised Learning via Redundancy Reduction
论文阅读
[Oct-15] A Simple Framework for Contrastive Learning of Visual Representations
论文阅读
[Oct-14] Contrastive Learning with Hard Negative Samples
论文阅读
[Oct-13] Debiased Contrastive Learning
论文阅读
[Oct-12] Understanding Contrastive Representation Learning through Alignment and Uniformity on the Hypersphere
数学
[Oct-11] 利普希茨连续条件(Lipschitz Continuity Condition)
Python
[Oct-10] 使用torch.autograd.grad实现对输入求导
论文阅读
[Oct-9] Data-Efficient Image Recognition with Contrastive Predictive Coding
论文阅读
[Oct-8] Representation Learning with Contrastive Predictive Coding
论文阅读
[Oct-7] Colorful Image Colorization
论文阅读
[Oct-6] Representation Learning by Learning to Count
论文阅读
[Oct-5] Unsupervised Learning of Visual Representations by Solving Jigsaw Puzzles
论文阅读
[Oct-4] Unsupervised Visual Representation Learning by Context Prediction
论文阅读
[Oct-3] Unsupervised Representation Learning by Predicting Image Rotations
论文阅读
[Oct-2] Discriminative Unsupervised Feature Learning with Exemplar Convolutional Neural Networks
深度学习
[Oct-1] 自监督学习(Self-Supervised Learning)
Sep-2022
论文阅读
[Sep-30] YOLOv6: A Single-Stage Object Detection Framework for Industrial Applications
数学
[Sep-23] 约束优化问题与对偶问题(Dual Problem)
数学
[Sep-22] 线性规划的对偶理论(Duality Theory)
论文阅读
[Sep-17] Flow Straight and Fast: Learning to Generate and Transfer Data with Rectified Flow
论文阅读
[Sep-16] Big Self-Supervised Models are Strong Semi-Supervised Learners
论文阅读
[Sep-15] FixMatch: Simplifying Semi-Supervised Learning with Consistency and Confidence
数学
[Sep-14] 行列式点过程(Determinantal Point Process)
论文阅读
[Sep-13] DivideMix: Learning with Noisy Labels as Semi-supervised Learning
论文阅读
[Sep-12] ReMixMatch: Semi-Supervised Learning with Distribution Alignment and Augmentation Anchoring
论文阅读
[Sep-11] MixMatch: A Holistic Approach to Semi-Supervised Learning
论文阅读
[Sep-10] Meta Pseudo Labels
论文阅读
[Sep-9] Pseudo-Labeling and Confirmation Bias in Deep Semi-Supervised Learning
论文阅读
[Sep-8] Label Propagation for Deep Semi-supervised Learning
论文阅读
[Sep-7] Unsupervised Data Augmentation for Consistency Training
论文阅读
[Sep-6] Interpolation Consistency Training for Semi-Supervised Learning
论文阅读
[Sep-5] Virtual Adversarial Training: A Regularization Method for Supervised and Semi-Supervised Learning
论文阅读
[Sep-4] Mean teachers are better role models: Weight-averaged consistency targets improve semi-supervised deep learning results
论文阅读
[Sep-3] Temporal Ensembling for Semi-Supervised Learning
论文阅读
[Sep-2] Regularization With Stochastic Transformations and Perturbations for Deep Semi-Supervised Learning
深度学习
[Sep-1] 半监督学习(Semi-Supervised Learning)
Aug-2022
论文阅读
[Aug-22] Deep Active Learning: Unified and Principled Method for Query and Training
论文阅读
[Aug-21] Discriminative Active Learning
论文阅读
[Aug-20] BatchBALD: Efficient and Diverse Batch Acquisition for Deep Bayesian Active Learning
论文阅读
[Aug-19] Batch Active Learning Using Determinantal Point Processes
论文阅读
[Aug-18] Batch Active Learning at Scale
论文阅读
[Aug-17] Deep Similarity-Based Batch Mode Active Learning with Exploration-Exploitation
论文阅读
[Aug-16] Cost-Effective Active Learning for Deep Image Classification
论文阅读
[Aug-15] Diverse mini-batch Active Learning
论文阅读
[Aug-14] Suggestive Annotation: A Deep Active Learning Framework for Biomedical Image Segmentation
论文阅读
[Aug-13] Bayesian Generative Active Deep Learning
论文阅读
[Aug-12] Generative Adversarial Active Learning
论文阅读
[Aug-11] Adversarial Active Learning for Deep Networks: a Margin Based Approach
论文阅读
[Aug-10] When Deep Learners Change Their Mind: Learning Dynamics for Active Learning
论文阅读
[Aug-9] Deep Batch Active Learning by Diverse, Uncertain Gradient Lower Bounds
论文阅读
[Aug-8] Active Learning for Convolutional Neural Networks: A Core-Set Approach
论文阅读
[Aug-7] Active Learning by Acquiring Contrastive Examples
论文阅读
[Aug-6] Minimax Active Learning
论文阅读
[Aug-5] Weight Uncertainty in Neural Networks
论文阅读
[Aug-4] Learning Loss for Active Learning
论文阅读
[Aug-3] Deep Bayesian Active Learning with Image Data
数学
[Aug-2] 深度学习中的不确定性(Uncertainty)
深度学习
[Aug-1] 主动学习(Active Learning)
Jul-2022
论文阅读
[Jul-31] SIoU Loss: More Powerful Learning for Bounding Box Regression
英语
[Jul-21] 40篇短文搞定3500个单词
数学
[Jul-20] 琴生不等式(Jenson’s Inequality)
Python
[Jul-11] 使用pydensecrf构造条件随机场
论文阅读
[Jul-10] YOLOv7: Trainable bag-of-freebies sets new state-of-the-art for real-time object detectors
论文阅读
[Jul-9] Comprehensive Guide to Ultralytics YOLOv5
论文阅读
[Jul-8] ViTPose: Simple Vision Transformer Baselines for Human Pose Estimation
论文阅读
[Jul-7] PolyLoss: A Polynomial Expansion Perspective of Classification Loss Functions
论文阅读
[Jul-6] RoFormer: Enhanced Transformer with Rotary Position Embedding
论文阅读
[Jul-5] Your Transformer May Not be as Powerful as You Expect
论文阅读
[Jul-4] Encoding word order in complex embeddings
论文阅读
[Jul-3] Self-Attention with Relative Position Representations
论文阅读
[Jul-2] Learning to Encode Position for Transformer with Continuous Dynamical Model
深度学习
[Jul-1] Transformer中的位置编码(Position Encoding)
Jun-2022
论文阅读
[Jun-30] Dual Contrastive Learning for Unsupervised Image-to-Image Translation
论文阅读
[Jun-29] Making the Invisible Visible: Action Recognition Through Walls and Occlusions
论文阅读
[Jun-26] Photorealistic Text-to-Image Diffusion Models with Deep Language Understanding
论文阅读
[Jun-25] GLIDE: Towards Photorealistic Image Generation and Editing with Text-Guided Diffusion Models
论文阅读
[Jun-24] Hierarchical Text-Conditional Image Generation with CLIP Latents
论文阅读
[Jun-23] Learning Longterm Representations for Person Re-Identification Using Radio Signals
论文阅读
[Jun-22] Variational Diffusion Models
论文阅读
[Jun-21] Poisson Flow Generative Models
数学
[Jun-20] 二分图与二分匹配(Bipartite Matching)
论文阅读
[Jun-19] Noether Networks: Meta-Learning Useful Conserved Quantities
论文阅读
[Jun-18] High-Resolution Image Synthesis with Latent Diffusion Models
论文阅读
[Jun-17] Cold Diffusion: Inverting Arbitrary Image Transforms Without Noise
论文阅读
[Jun-16] O-GAN: Extremely Concise Approach for Auto-Encoding Generative Adversarial Networks
论文阅读
[Jun-15] Alias-Free Generative Adversarial Networks
论文阅读
[Jun-14] Semi-Supervised Learning with Generative Adversarial Networks
论文阅读
[Jun-13] ClusterGAN : Latent Space Clustering in Generative Adversarial Networks
论文阅读
[Jun-12] Deep Symbolic Regression for Recurrent Sequences
论文阅读
[Jun-11] Training Generative Adversarial Networks with Limited Data
论文阅读
[Jun-10] Classifier-Free Diffusion Guidance
论文阅读
[Jun-9] More Control for Free! Image Synthesis with Semantic Diffusion Guidance
论文阅读
[Jun-8] Diffusion Models Beat GANs on Image Synthesis
论文阅读
[Jun-7] Estimating the Optimal Covariance with Imperfect Mean in Diffusion Probabilistic Models
论文阅读
[Jun-6] Analytic-DPM: an Analytic Estimate of the Optimal Reverse Variance in Diffusion Probabilistic Models
论文阅读
[Jun-5] Score-Based Generative Modeling through Stochastic Differential Equations
论文阅读
[Jun-4] Denoising Diffusion Implicit Models
论文阅读
[Jun-3] Improved Denoising Diffusion Probabilistic Models
论文阅读
[Jun-2] Denoising Diffusion Probabilistic Models
深度学习
[Jun-1] 扩散模型(Diffusion Model)
May-2022
论文阅读
[May-31] Analyzing and Improving the Image Quality of StyleGAN
论文阅读
[May-30] A Style-Based Generator Architecture for Generative Adversarial Networks
论文阅读
[May-29] Do As I Can, Not As I Say: Grounding Language in Robotic Affordances
论文阅读
[May-28] On Self Modulation for Generative Adversarial Networks
论文阅读
[May-27] Large Scale GAN Training for High Fidelity Natural Image Synthesis
论文阅读
[May-26] Taming Transformers for High-Resolution Image Synthesis
论文阅读
[May-25] Self-Attention Generative Adversarial Networks
论文阅读
[May-24] cGANs with Projection Discriminator
论文阅读
[May-23] StackGAN: Text to Photo-realistic Image Synthesis with Stacked Generative Adversarial Networks
论文阅读
[May-22] SinGAN: Learning a Generative Model from a Single Natural Image
论文阅读
[May-21] Progressive Growing of GANs for Improved Quality, Stability, and Variation
论文阅读
[May-20] Semi-Supervised Learning with Context-Conditional Generative Adversarial Networks
论文阅读
[May-19] Context Encoders: Feature Learning by Inpainting
论文阅读
[May-18] Semantic Image Synthesis with Spatially-Adaptive Normalization
论文阅读
[May-17] Reusing Discriminators for Encoding: Towards Unsupervised Image-to-Image Translation
数学
[May-16] 最优传输(Optimal Transport)问题与Wasserstein距离
论文阅读
[May-15] Softmax GAN
论文阅读
[May-14] On Convergence and Stability of GANs
论文阅读
[May-13] Invertible Residual Networks
论文阅读
[May-12] Flow++: Improving Flow-Based Generative Models with Variational Dequantization and Architecture Design
论文阅读
[May-11] Improving Variational Inference with Inverse Autoregressive Flow
论文阅读
[May-10] Contrastive Learning for Unpaired Image-to-Image Translation
论文阅读
[May-9] TFPose: Direct Human Pose Estimation with Transformers
论文阅读
[May-8] Masked Autoregressive Flow for Density Estimation
论文阅读
[May-7] Variational Inference with Normalizing Flows
论文阅读
[May-6] Unsupervised Learning for Human Sensing Using Radio Signals
Python
[May-5] 曲线的平滑处理方法
论文阅读
[May-4] Glow: Generative Flow with Invertible 1x1 Convolutions
论文阅读
[May-3] Density estimation using Real NVP
论文阅读
[May-2] NICE: Non-linear Independent Components Estimation
深度学习
[May-1] 流模型(Flow-based Model)
Apr-2022
数学
[Apr-30] 随机变量的变量替换定理(Change of Variable Theorem)
论文阅读
[Apr-29] GANILLA: Generative Adversarial Networks for Image to Illustration Translation
论文阅读
[Apr-28] Rethinking the Truly Unsupervised Image-to-Image Translation
论文阅读
[Apr-27] High-Resolution Photorealistic Image Translation in Real-Time: A Laplacian Pyramid Translation Network
论文阅读
[Apr-26] Multimodal Unsupervised Image-to-Image Translation
论文阅读
[Apr-25] Simple yet Effective Way for Improving the Performance of GAN
数学
[Apr-24] 概率分布的重参数化(Reparameterization)技巧
数学
[Apr-23] 超球面上的von Mises-Fisher(vMF)分布
论文阅读
[Apr-22] f-VAEs: Improve VAEs with Conditional Flows
论文阅读
[Apr-21] Temporal Difference Variational Auto-Encoder
论文阅读
[Apr-20] NVAE: A Deep Hierarchical Variational Autoencoder
论文阅读
[Apr-19] Hyperspherical Variational Auto-Encoders
论文阅读
[Apr-18] A Batch Normalized Inference Network Keeps the KL Vanishing Away
论文阅读
[Apr-17] Variational Inference of Disentangled Latent Concepts from Unlabeled Observations
论文阅读
[Apr-16] Structured Disentangled Representations
论文阅读
[Apr-15] Disentangling by Factorising
论文阅读
[Apr-14] Sliced-Wasserstein Autoencoder: An Embarrassingly Simple Generative Model
论文阅读
[Apr-13] Log Hyperbolic Cosine Loss Improves Variational Auto-Encoder
论文阅读
[Apr-12] Learning to Generate Images with Perceptual Similarity Metrics
论文阅读
[Apr-11] Learning Disentangled Joint Continuous and Discrete Representations
论文阅读
[Apr-10] Categorical Reparameterization with Gumbel-Softmax
论文阅读
[Apr-9] Deep Feature Consistent Variational Autoencoder
论文阅读
[Apr-8] Tighter Variational Bounds are Not Necessarily Better
论文阅读
[Apr-7] Importance Weighted Autoencoders
论文阅读
[Apr-6] Single-Shot Multi-Person 3D Pose Estimation From Monocular RGB
论文阅读
[Apr-5] Isolating Sources of Disentanglement in Variational Autoencoders
论文阅读
[Apr-4] Wasserstein Auto-Encoders
论文阅读
[Apr-3] Variational methods for Conditional Multimodal Learning: Generating Human Faces from Attributes
论文阅读
[Apr-2] Learning Structured Output Representation using Deep Conditional Generative Models
深度学习
[Apr-1] 变分自编码器(Variational Autoencoder)
Mar-2022
论文阅读
[Mar-31] Exploring and Exploiting Hubness Priors for High-Quality GAN Latent Sampling
论文阅读
[Mar-30] Demystifying MMD GANs
论文阅读
[Mar-29] Fisher GAN
论文阅读
[Mar-28] MMD GAN: Towards Deeper Understanding of Moment Matching Network
论文阅读
[Mar-27] Generative Moment Matching Networks
论文阅读
[Mar-26] McGan: Mean and Covariance Feature Matching GAN
论文阅读
[Mar-25] A Note on the Inception Score
论文阅读
[Mar-24] GANs Trained by a Two Time-Scale Update Rule Converge to a Local Nash Equilibrium
论文阅读
[Mar-23] Which Training Methods for GANs do actually Converge?
论文阅读
[Mar-22] Deep Generative Image Models using a Laplacian Pyramid of Adversarial Networks
论文阅读
[Mar-21] Unsupervised Image-to-Image Translation Networks
论文阅读
[Mar-20] StarGAN v2: Diverse Image Synthesis for Multiple Domains
论文阅读
[Mar-19] StarGAN: Unified Generative Adversarial Networks for Multi-Domain Image-to-Image Translation
论文阅读
[Mar-18] Toward Multimodal Image-to-Image Translation
论文阅读
[Mar-17] DualGAN: Unsupervised Dual Learning for Image-to-Image Translation
论文阅读
[Mar-16] Learning to Discover Cross-Domain Relations with Generative Adversarial Networks
论文阅读
[Mar-15] Unsupervised Pixel-Level Domain Adaptation with Generative Adversarial Networks
数学
[Mar-14] 圆周率(Ratio of Circumference to Diameter)的计算
论文阅读
[Mar-13] Competition-Level Code Generation with AlphaCode
论文阅读
[Mar-12] Evaluating Large Language Models Trained on Code
论文阅读
[Mar-11] Self-Correction for Human Parsing
论文阅读
[Mar-10] Image-to-Image Translation with Conditional Adversarial Networks
论文阅读
[Mar-9] Gradientless Descent: High-Dimensional Zeroth-Order Optimization
论文阅读
[Mar-8] Coupled Generative Adversarial Networks
论文阅读
[Mar-7] Designing GANs: A Likelihood Ratio Approach
论文阅读
[Mar-6] InfoGAN: Interpretable Representation Learning by Information Maximizing Generative Adversarial Nets
论文阅读
[Mar-5] Transformer Quality in Linear Time
论文阅读
[Mar-4] Step-size Adaptation Using Exponentiated Gradient Updates
论文阅读
[Mar-3] Conditional Image Synthesis With Auxiliary Classifier GANs
论文阅读
[Mar-2] Conditional Generative Adversarial Nets
Python
[Mar-1] 使用opencv-python(cv2)库进行相机标定
Feb-2022
论文阅读
[Feb-28] Boundary-Seeking Generative Adversarial Networks
论文阅读
[Feb-27] BEGAN: Boundary Equilibrium Generative Adversarial Networks
论文阅读
[Feb-26] Efficient Through-wall Human Pose Reconstruction Using UWB MIMO Radar
论文阅读
[Feb-25] Loss-Sensitive Generative Adversarial Networks on Lipschitz Densities
论文阅读
[Feb-24] MAGAN: Margin Adaptation for Generative Adversarial Networks
论文阅读
[Feb-23] Maximum Entropy Generators for Energy-Based Models
论文阅读
[Feb-22] GAN-QP: A Novel GAN Framework without Gradient Vanishing and Lipschitz Constraint
论文阅读
[Feb-21] The relativistic discriminator: a key element missing from standard GAN
论文阅读
[Feb-20] Adversarial Autoencoders
论文阅读
[Feb-19] Gradients without Backpropagation
论文阅读
[Feb-18] Adversarial Feature Learning
论文阅读
[Feb-17] Autoencoding beyond pixels using a learned similarity metric
论文阅读
[Feb-16] Energy-based Generative Adversarial Network
论文阅读
[Feb-15] Least Squares Generative Adversarial Networks
论文阅读
[Feb-14] Unpaired Image-to-Image Translation using Cycle-Consistent Adversarial Networks
论文阅读
[Feb-13] Wasserstein GANs Work Because They Fail (to Approximate the Wasserstein Distance)
论文阅读
[Feb-12] How Well Do WGANs Estimate the Wasserstein Metric?
论文阅读
[Feb-11] GraN-GAN: Piecewise Gradient Normalization for Generative Adversarial Networks
论文阅读
[Feb-10] Gradient Normalization for Generative Adversarial Networks
论文阅读
[Feb-9] Wasserstein Divergence for GANs
论文阅读
[Feb-8] Spectral Normalization for Generative Adversarial Networks
论文阅读
[Feb-7] f-GAN: Training Generative Neural Samplers using Variational Divergence Minimization
论文阅读
[Feb-6] Improved Training of Wasserstein GANs
论文阅读
[Feb-5] Unsupervised Representation Learning with Deep Convolutional Generative Adversarial Networks
论文阅读
[Feb-4] Wasserstein GAN
论文阅读
[Feb-3] Towards Principled Methods for Training Generative Adversarial Networks
论文阅读
[Feb-2] Improved Techniques for Training GANs
深度学习
[Feb-1] 生成对抗网络(Generative Adversarial Network)
Jan-2022
论文阅读
[Jan-8] Advancing mathematics by guiding human intuition with AI
机器学习
[Jan-6] Self-Organizing Map(SOM)：自组织映射神经网络
Dec-2021
论文阅读
[Dec-10] Swin Transformer: Hierarchical Vision Transformer using Shifted Windows
论文阅读
[Dec-9] Masked Autoencoders Are Scalable Vision Learners
论文阅读
[Dec-2] Variational Adversarial Active Learning
论文阅读
[Dec-1] Robust and Generalizable Visual Representation Learning via Random Convolutions
Nov-2021
Python
[Nov-30] 使用torchvision.transforms进行图像增强
论文阅读
[Nov-29] TrivialAugment: Tuning-free Yet State-of-the-Art Data Augmentation
论文阅读
[Nov-28] RandAugment: Practical automated data augmentation with a reduced search space
论文阅读
[Nov-27] AutoAugment: Learning Augmentation Policies from Data
论文阅读
[Nov-26] Random Erasing Data Augmentation
论文阅读
[Nov-19] Squareplus: A Softplus-Like Algebraic Rectifier
论文阅读
[Nov-18] Activate or Not: Learning Customized Activation
论文阅读
[Nov-17] SMU: smooth activation function for deep networks using smoothing maximum technique
数学
[Nov-16] 函数的光滑化(Smoothing)
论文阅读
[Nov-9] MicroNet: Towards Image Recognition with Extremely Low FLOPs
论文阅读
[Nov-8] GhostNet: More Features from Cheap Operations
论文阅读
[Nov-5] SAU: Smooth activation function using convolution with approximate identities
Oct-2021
论文阅读
[Oct-28] ZerO Initialization: Initializing Neural Networks with only Zeros and Ones
论文阅读
[Oct-27] Dynamic ReLU
论文阅读
[Oct-26] Learning Activation Functions to Improve Deep Neural Networks
论文阅读
[Oct-25] Orthogonal-Padé Activation Functions: Trainable Activation functions for smooth and faster convergence in deep networks
论文阅读
[Oct-24] Padé Activation Units: End-to-end Learning of Flexible Activation Functions in Deep Networks
论文阅读
[Oct-23] Maxout Networks
论文阅读
[Oct-22] Learning specialized activation functions with the Piecewise Linear Unit
论文阅读
[Oct-18] SmoothNet: A Plug-and-Play Network for Refining Human Poses in Videos
论文阅读
[Oct-17] Pose for Everything: Towards Category-Agnostic Pose Estimation
论文阅读
[Oct-16] Localization with Sampling-Argmax
论文阅读
[Oct-15] Poseur: Direct Human Pose Regression with Transformers
论文阅读
[Oct-14] Next-Generation Pose Detection with MoveNet and TensorFlow
论文阅读
[Oct-13] Low-resolution Human Pose Estimation
论文阅读
[Oct-12] TOOD: Task-aligned One-stage Object Detection
论文阅读
[Oct-11] Unifying Nonlocal Blocks for Neural Networks
论文阅读
[Oct-10] Attention Augmented Convolutional Networks
论文阅读
[Oct-9] Dynamic Task Prioritization for Multitask Learning
论文阅读
[Oct-8] Outrageously Large Neural Networks: The Sparsely-Gated Mixture-of-Experts Layer
论文阅读
[Oct-7] Region-based Non-local Operation for Video Classification
论文阅读
[Oct-6] Exploring Self-attention for Image Recognition
论文阅读
[Oct-5] Image Super-Resolution with Non-Local Sparse Attention
论文阅读
[Oct-4] Polarized Self-Attention: Towards High-quality Pixel-wise Regression
论文阅读
[Oct-3] DMSANet: Dual Multi Scale Attention Network
论文阅读
[Oct-2] SimAM: A Simple, Parameter-Free Attention Module for Convolutional Neural Networks
论文阅读
[Oct-1] Residual Attention: A Simple but Effective Method for Multi-Label Recognition
Sep-2021
机器学习
[Sep-30] 局部保留投影(Locality Preserving Projection, LPP)
论文阅读
[Sep-29] Sluice networks: Learning what to share between loosely related tasks
论文阅读
[Sep-28] Cross-stitch Networks for Multi-task Learning
论文阅读
[Sep-27] Fully-adaptive Feature Sharing in Multi-Task Networks with Applications in Person Attribute Classification
论文阅读
[Sep-26] Learning Multiple Tasks with Multilinear Relationship Networks
数学
[Sep-25] 多目标优化的帕累托最优(Pareto Optimality)
机器学习
[Sep-24] 一致流形近似与投影(Uniform Manifold Approximation and Projection, UMAP)
机器学习
[Sep-23] t分布随机近邻嵌入(t-distributed Stochastic Neighbor Embedding, t-SNE)
论文阅读
[Sep-22] IGCV2: Interleaved Structured Sparse Convolutional Neural Networks
论文阅读
[Sep-21] Interleaved Group Convolutions for Deep Neural Networks
论文阅读
[Sep-20] ChannelNets: Compact and Efficient Convolutional Neural Networks via Channel-Wise Convolutions
论文阅读
[Sep-19] ShuffleNet V2: Practical Guidelines for Efficient CNN Architecture Design
论文阅读
[Sep-18] ShuffleNet: An Extremely Efficient Convolutional Neural Network for Mobile Devices
论文阅读
[Sep-17] SqueezeNext: Hardware-Aware Neural Network Design
论文阅读
[Sep-16] SqueezeNet: AlexNet-level accuracy with 50x fewer parameters and <0.5MB model size
论文阅读
[Sep-15] Searching for MobileNetV3
论文阅读
[Sep-14] MobileNetV2: Inverted Residuals and Linear Bottlenecks
论文阅读
[Sep-13] MobileNets: Efficient Convolutional Neural Networks for Mobile Vision Applications
论文阅读
[Sep-12] EfficientNetV2: Smaller Models and Faster Training
论文阅读
[Sep-11] EfficientNet: Rethinking Model Scaling for Convolutional Neural Networks
深度学习
[Sep-10] 轻量级(LightWeight)卷积神经网络
论文阅读
[Sep-8] GradNorm: Gradient Normalization for Adaptive Loss Balancing in Deep Multitask Networks
论文阅读
[Sep-7] Loss-Balanced Task Weighting to Reduce Negative Transfer in Multi-Task Learning
论文阅读
[Sep-6] End-to-End Multi-Task Learning with Attention
论文阅读
[Sep-5] Multi-Task Learning Using Uncertainty to Weigh Losses for Scene Geometry and Semantics
论文阅读
[Sep-4] Searching for Activation Functions
论文阅读
[Sep-3] The Quest for the Golden Activation Function
论文阅读
[Sep-2] Self-Normalizing Neural Networks
Python
[Sep-1] 使用sympy.solve求解方程
Aug-2021
论文阅读
[Aug-31] Empirical Evaluation of Rectified Activations in Convolutional Network
论文阅读
[Aug-30] Delving Deep into Rectifiers: Surpassing Human-Level Performance on ImageNet Classification
论文阅读
[Aug-29] Rectifier Nonlinearities Improve Neural Network Acoustic Models
深度学习
[Aug-28] 多任务学习(Multi-Task Learning)
论文阅读
[Aug-27] Training Deeper Convolutional Networks with Deep Supervision
论文阅读
[Aug-26] Deeply-Supervised Nets
论文阅读
[Aug-25] Fast and Accurate Deep Network Learning by Exponential Linear Units (ELUs)
论文阅读
[Aug-24] Bridging Nonlinearities and Stochastic Regularizers with Gaussian Error Linear Units
Python
[Aug-23] 使用scipy.optimize.minimize求解非线性规划
论文阅读
[Aug-22] Continuously Differentiable Exponential Linear Units
论文阅读
[Aug-21] Mish: A Self Regularized Non-Monotonic Activation Function
数学
[Aug-20] 泰勒公式(Taylor Formula)
论文阅读
[Aug-19] XLNet: Generalized Autoregressive Pretraining for Language Understanding
论文阅读
[Aug-18] MASS: Masked Sequence to Sequence Pre-training for Language Generation
论文阅读
[Aug-17] Unified Language Model Pre-training for Natural Language Understanding and Generation
论文阅读
[Aug-16] RoBERTa: A Robustly Optimized BERT Pretraining Approach
论文阅读
[Aug-15] Efficient Attention: Attention with Linear Complexities
论文阅读
[Aug-14] Longformer: The Long-Document Transformer
论文阅读
[Aug-13] Linformer: Self-Attention with Linear Complexity
论文阅读
[Aug-12] Rethinking Attention with Performers
论文阅读
[Aug-11] Reformer: The Efficient Transformer
论文阅读
[Aug-10] Transformers are RNNs: Fast Autoregressive Transformers with Linear Attention
论文阅读
[Aug-9] Beyond Self-attention: External Attention using Two Linear Layers for Visual Tasks
数学
[Aug-8] 二进制乘法的Mitchell近似
论文阅读
[Aug-6] ResMLP: Feedforward networks for image classification with data-efficient training
论文阅读
[Aug-6] Do You Even Need Attention? A Stack of Feed-Forward Layers Does Surprisingly Well on ImageNet
论文阅读
[Aug-5] MLP-Mixer: An all-MLP Architecture for Vision
论文阅读
[Aug-4] Simpler, Faster, Stronger: Breaking The log-K Curse On Contrastive Learners With FlatNCE
论文阅读
[Aug-3] CompConv: A Compact Convolution Module for Efficient Feature Learning
论文阅读
[Aug-2] Integrating Circle Kernels into Convolutional Neural Networks
论文阅读
[Aug-1] YOLOX: Exceeding YOLO Series in 2021
Jul-2021
机器学习
[Jul-31] 局部线性嵌入(Locally Linear Embedding, LLE)
机器学习
[Jul-30] 等度量映射(Isometric Mapping, ISOMAP)
机器学习
[Jul-29] 多类别(Multiclass)与多标签(Multilabel)分类
机器学习
[Jul-28] 多维缩放(Multiple Dimensional Scaling, MDS)
机器学习
[Jul-27] 核主成分分析(Kernelized Principal Component Analysis, KPCA)
论文阅读
[Jul-24] Human Pose Regression with Residual Log-likelihood Estimation
机器学习
[Jul-23] Kernel Method：核方法
机器学习
[Jul-22] 集成学习中的误差-分歧分解(Error-Ambiguity Decomposition)
机器学习
[Jul-21] 集成学习中的多样性度量(Diversity Measure)
机器学习
[Jul-20] Maximum Entropy：最大熵模型
论文阅读
[Jul-19] BBN: Bilateral-Branch Network with Cumulative Learning for Long-Tailed Visual Recognition
论文阅读
[Jul-17] Actions as Moving Points
论文阅读
[Jul-16] MultiSports: A Multi-Person Video Dataset of Spatio-Temporally Localized Sports Actions
深度学习
[Jul-15] 时空动作检测(Spatio-Temporal Action Detection)
论文阅读
[Jul-14] Equalization Loss v2: A New Gradient Balance Approach for Long-tailed Object Detection
论文阅读
[Jul-13] Generating Long Sequences with Sparse Transformers
深度学习
[Jul-12] 降低Transformer的计算复杂度
论文阅读
[Jul-10] R-Drop: Regularized Dropout for Neural Networks
数学
[Jul-9] 机器学习中的假设检验(Hypothesis Test)
论文阅读
[Jul-8] Descending through a Crowded Valley - Benchmarking Deep Learning Optimizers
论文阅读
[Jul-7] Addressing Some Limitations of Transformers with Feedback Memory
深度学习
[Jul-2] 卷积神经网络中的池化(Pooling)层
论文阅读
[Jul-1] Language Models are Open Knowledge Graphs
Jun-2021
论文阅读
[Jun-30] Supermasks in Superposition
论文阅读
[Jun-29] UNet++: A Nested U-Net Architecture for Medical Image Segmentation
论文阅读
[Jun-28] Fourier Neural Operator for Parametric Partial Differential Equations
论文阅读
[Jun-27] Gradient Centralization: A New Optimization Technique for Deep Neural Networks
论文阅读
[Jun-25] PeCLR: Self-Supervised 3D Hand Pose Estimation from monocular RGB via Equivariant Contrastive Learning
Python
[Jun-24] 绘制混淆矩阵
论文阅读
[Jun-23] GIRAFFE: Representing Scenes as Compositional Generative Neural Feature Fields
数学
[Jun-22] 瑞利商(Rayleigh Quotient)与广义(Generalized)瑞利商
论文阅读
[Jun-21] GAN-BERT: Generative Adversarial Learning for Robust Text Classification with a Bunch of Labeled Examples
Python
[Jun-20] MMDetection 用户笔记
论文阅读
[Jun-20] HR-NAS: Searching Efficient High-Resolution Neural Architectures with Lightweight Transformers
论文阅读
[Jun-19] Learning Spatial Fusion for Single-Shot Object Detection
论文阅读
[Jun-18] Region Proposal by Guided Anchoring
论文阅读
[Jun-17] Gradient Harmonized Single-stage Detector
论文阅读
[Jun-16] HAMBox: Delving into Online High-quality Anchors Mining for Detecting Outer Faces
Python
[Jun-15] Albumentations: 图像的数据增强库
论文阅读
[Jun-14] Overcoming Classifier Imbalance for Long-tail Object Detection with Balanced Group Softmax
论文阅读
[Jun-13] Deformable DETR: Deformable Transformers for End-to-End Object Detection
论文阅读
[Jun-12] Segmented convolutional gated recurrent neural networks for human activity recognition in ultra-wideband radar
论文阅读
[Jun-11] Human Motion Recognition With Limited Radar Micro-Doppler Signatures
论文阅读
[Jun-10] Object Detection from Video Tubelets with Convolutional Neural Networks
论文阅读
[Jun-9] Action Tubelet Detector for Spatio-Temporal Action Localization
论文阅读
[Jun-8] Y-Net: Joint Segmentation and Classification for Diagnosis of Breast Biopsy Images
论文阅读
[Jun-7] W-Net: A Deep Model for Fully Unsupervised Image Segmentation
论文阅读
[Jun-6] M-Net: A Convolutional Neural Network for Deep Brain Structure Segmentation
论文阅读
[Jun-5] V-Net: Fully Convolutional Neural Networks for Volumetric Medical Image Segmentation
论文阅读
[Jun-4] Human motion recognition exploiting radar with stacked recurrent neural network
论文阅读
[Jun-3] Extracting Training Data from Large Language Models
论文阅读
[Jun-2] EfficientDet: Scalable and Efficient Object Detection
论文阅读
[Jun-1] Learning from Noisy Anchors for One-stage Object Detection
May-2021
论文阅读
[May-31] Poly-YOLO: higher speed, more precise detection and instance segmentation for YOLOv3
论文阅读
[May-30] Dynamic R-CNN: Towards High Quality Object Detection via Dynamic Training
论文阅读
[May-29] Sparse R-CNN: End-to-End Object Detection with Learnable Proposals
论文阅读
[May-28] RepPoints: Point Set Representation for Object Detection
论文阅读
[May-27] AutoAssign: Differentiable Label Assignment for Dense Object Detection
论文阅读
[May-26] Generalized Focal Loss V2: Learning Reliable Localization Quality Estimation for Dense Object Detection
论文阅读
[May-25] VarifocalNet: An IoU-aware Dense Object Detector
论文阅读
[May-24] Soft Anchor-Point Object Detection
论文阅读
[May-23] Bridging the Gap Between Anchor-based and Anchor-free Detection via Adaptive Training Sample Selection
论文阅读
[May-22] Libra R-CNN: Towards Balanced Learning for Object Detection
论文阅读
[May-21] Generalized Focal Loss: Learning Qualified and Distributed Bounding Boxes for Dense Object Detection
深度学习
[May-20] 图像长尾分布(Long-Tail Distribution)问题
论文阅读
[May-19] Every Model Learned by Gradient Descent Is Approximately a Kernel Machine
论文阅读
[May-18] Unsupervised Adversarial Domain Adaptation for Micro-Doppler Based Human Activity Classification
论文阅读
[May-17] Unsupervised Domain Adaptation for Micro-Doppler Human Motion Classification via Feature Fusion
论文阅读
[May-16] Through-Wall Human Motion Recognition Based on Transfer Learning and Ensemble Learning
论文阅读
[May-15] Cross-regional oil palm tree counting and detection via a multi-level attention domain adaptation network
论文阅读
[May-14] Cross-Regional Oil Palm Tree Detection
论文阅读
[May-13] Radar-Based Human Activity Recognition With 1-D Dense Attention Network
论文阅读
[May-12] Lite-HRNet: A Lightweight High-Resolution Network
论文阅读
[May-8] Switch Transformers: Scaling to Trillion Parameter Models with Simple and Efficient Sparsity
论文阅读
[May-4] Weakly-Supervised Mesh-Convolutional Hand Reconstruction in the Wild
论文阅读
[May-3] Numerical Coordinate Regression with Convolutional Neural Networks
论文阅读
[May-2] Removing the Bias of Integral Pose Regression
论文阅读
[May-1] Lite Pose: Efficient Architecture Design for 2D Human Pose Estimation
Apr-2021
论文阅读
[Apr-30] Pixel-in-Pixel Net: Towards Efficient Facial Landmark Detection in the Wild
论文阅读
[Apr-29] Nyströmformer: A Nyström-Based Algorithm for Approximating Self-Attention
论文阅读
[Apr-28] SimCC: a Simple Coordinate Classification Perspective for Human Pose Estimation
论文阅读
[Apr-27] TokenPose: Learning Keypoint Tokens for Human Pose Estimation
论文阅读
[Apr-26] Online Knowledge Distillation for Efficient Pose Estimation
论文阅读
[Apr-25] Integral Human Pose Regression
论文阅读
[Apr-24] Distribution-Aware Coordinate Representation for Human Pose Estimation
论文阅读
[Apr-23] The Devil is in the Details: Delving into Unbiased Data Processing for Human Pose Estimation
论文阅读
[Apr-22] AID: Pushing the Performance Boundary of Human Pose Estimation with Information Dropping Augmentation
论文阅读
[Apr-21] High-Performance Large-Scale Image Recognition Without Normalization
论文阅读
[Apr-20] PoseAug: A Differentiable Pose Augmentation Framework for 3D Human Pose Estimation
论文阅读
[Apr-19] 3D Human Pose Estimation = 2D Pose Estimation + Matching
论文阅读
[Apr-18] Camera Distance-aware Top-down Approach for 3D Multi-person Pose Estimation from a Single RGB Image
论文阅读
[Apr-17] Coarse-to-Fine Volumetric Prediction for Single-Image 3D Human Pose
论文阅读
[Apr-16] VNect: Real-time 3D Human Pose Estimation with a Single RGB Camera
论文阅读
[Apr-15] 3D Human Pose Estimation from Monocular Images with Deep Convolutional Neural Network
论文阅读
[Apr-14] Deep High-Resolution Representation Learning for Human Pose Estimation
论文阅读
[Apr-13] Rethinking on Multi-Stage Networks for Human Pose Estimation
论文阅读
[Apr-12] Cascaded Pyramid Network for Multi-Person Pose Estimation
论文阅读
[Apr-11] DeepCut: Joint Subset Partition and Labeling for Multi Person Pose Estimation
论文阅读
[Apr-10] Associative Embedding: End-to-End Learning for Joint Detection and Grouping
论文阅读
[Apr-9] RMPE: Regional Multi-person Pose Estimation
论文阅读
[Apr-8] Realtime Multi-Person 2D Pose Estimation using Part Affinity Fields
论文阅读
[Apr-7] Learning Feature Pyramids for Human Pose Estimation
论文阅读
[Apr-6] Multi-Context Attention for Human Pose Estimation
论文阅读
[Apr-5] Chained Predictions Using Convolutional Neural Networks
论文阅读
[Apr-4] Convolutional Pose Machines
论文阅读
[Apr-3] Stacked Hourglass Networks for Human Pose Estimation
论文阅读
[Apr-2] DeBERTa: Decoding-enhanced BERT with Disentangled Attention
论文阅读
[Apr-1] DeepPose: Human Pose Estimation via Deep Neural Networks
Mar-2021
论文阅读
[Mar-30] FCOS: A Simple and Strong Anchor-free Object Detector
论文阅读
[Mar-29] AMASS: Archive of Motion Capture as Surface Shapes
论文阅读
[Mar-28] Is Attention Better Than Matrix Decomposition?
论文阅读
[Mar-27] SegNeXt: Rethinking Convolutional Attention Design for Semantic Segmentation
论文阅读
[Mar-26] Object-Contextual Representations for Semantic Segmentation
论文阅读
[Mar-25] Boundary loss for highly unbalanced segmentation
Python
[Mar-24] 计算模型的参数量(Params)和运算量(FLOPs)
论文阅读
[Mar-23] Objects as Points
Python
[Mar-22] Argmax与SoftArgmax
论文阅读
[Mar-21] Focal Loss for Dense Object Detection
论文阅读
[Mar-20] SSD: Single Shot MultiBox Detector
论文阅读
[Mar-19] YOLOv3: An Incremental Improvement
论文阅读
[Mar-18] Revisiting ResNets: Improved Training and Scaling Strategies
论文阅读
[Mar-17] YOLO9000: Better, Faster, Stronger
论文阅读
[Mar-16] You Only Look Once: Unified, Real-Time Object Detection
论文阅读
[Mar-15] KeepAugment: A Simple Information-Preserving Data Augmentation Approach
论文阅读
[Mar-12] Involution: Inverting the Inherence of Convolution for Visual Recognition
论文阅读
[Mar-11] Rethinking the Inception Architecture for Computer Vision
论文阅读
[Mar-10] Cascade R-CNN: Delving into High Quality Object Detection
论文阅读
[Mar-9] Faster R-CNN: Towards Real-Time Object Detection with Region Proposal Networks
论文阅读
[Mar-8] Transformer in Transformer
论文阅读
[Mar-7] Fast R-CNN
论文阅读
[Mar-6] Coordinate Attention for Efficient Mobile Network Design
论文阅读
[Mar-5] Towards 3D Human Pose Construction Using WiFi
论文阅读
[Mar-4] Person-in-WiFi: Fine-grained Person Perception using WiFi
数学
[Mar-3] 距离度量(Distance Metric)方法
论文阅读
[Mar-2] TransGAN: Two Transformers Can Make One Strong GAN
论文阅读
[Mar-1] Rich feature hierarchies for accurate object detection and semantic segmentation
Feb-2021
论文阅读
[Feb-28] Unified Perceptual Parsing for Scene Understanding
论文阅读
[Feb-27] mm-Pose: Real-Time Human Skeletal Posture Estimation using mmWave Radars and CNNs
论文阅读
[Feb-26] PSANet: Point-wise Spatial Attention Network for Scene Parsing
论文阅读
[Feb-25] Through-Wall Human Pose Reconstruction via UWB MIMO Radar and 3D CNN
论文阅读
[Feb-24] Adaptive Pyramid Context Network for Semantic Segmentation
论文阅读
[Feb-23] Dynamic Multi-Scale Filters for Semantic Segmentation
论文阅读
[Feb-22] DFANet: Deep Feature Aggregation for Real-Time Semantic Segmentation
论文阅读
[Feb-21] Context Encoding for Semantic Segmentation
论文阅读
[Feb-20] Attention U-Net: Learning Where to Look for the Pancreas
论文阅读
[Feb-19] RefineNet: Multi-Path Refinement Networks for High-Resolution Semantic Segmentation
论文阅读
[Feb-18] Pyramid Scene Parsing Network
论文阅读
[Feb-17] Encoder-Decoder with Atrous Separable Convolution for Semantic Image Segmentation
论文阅读
[Feb-16] Rethinking Atrous Convolution for Semantic Image Segmentation
论文阅读
[Feb-15] DeepLab: Semantic Image Segmentation with Deep Convolutional Nets, Atrous Convolution, and Fully Connected CRFs
论文阅读
[Feb-14] Semantic Image Segmentation with Deep Convolutional Nets and Fully Connected CRFs
论文阅读
[Feb-13] U-Net: Convolutional Networks for Biomedical Image Segmentation
论文阅读
[Feb-12] RF-Based 3D Skeletons
论文阅读
[Feb-11] SegNet: A Deep Convolutional Encoder-Decoder Architecture for Image Segmentation
论文阅读
[Feb-10] A Survey on Visual Transformer
论文阅读
[Feb-9] Pre-Trained Image Processing Transformer
论文阅读
[Feb-8] Fully Convolutional Networks for Semantic Segmentation
论文阅读
[Feb-7] Augmentation for small object detection
论文阅读
[Feb-6] A Survey of Handy See-Through Wall Technology
论文阅读
[Feb-5] RepVGG: Making VGG-style ConvNets Great Again
论文阅读
[Feb-4] Image Transformer
论文阅读
[Feb-3] Through-Wall Pose Imaging in Real-Time with a Many-to-Many Encoder/Decoder Paradigm
论文阅读
[Feb-2] Expressive Body Capture: 3D Hands, Face, and Body from a Single Image
Jan-2021
论文阅读
[Jan-31] Bottleneck Transformers for Visual Recognition
论文阅读
[Jan-30] SA-Net: Shuffle Attention for Deep Convolutional Neural Networks
论文阅读
[Jan-29] 3D Imaging of Moving Targets for Ultra-wideband MIMO Through-wall Radar System
论文阅读
[Jan-28] Panoptic Feature Pyramid Networks
论文阅读
[Jan-27] BiSeNet V2: Bilateral Network with Guided Aggregation for Real-time Semantic Segmentation
论文阅读
[Jan-26] BiSeNet: Bilateral Segmentation Network for Real-time Semantic Segmentation
论文阅读
[Jan-25] GRUU-Net: Integrated convolutional and gated recurrent neural network for cell segmentation
论文阅读
[Jan-24] PointRend: Image Segmentation as Rendering
论文阅读
[Jan-23] K-Net: Towards Unified Image Segmentation
论文阅读
[Jan-22] Ordered Neurons: Integrating Tree Structures into Recurrent Neural Networks
论文阅读
[Jan-21] Balanced Meta-Softmax for Long-Tailed Visual Recognition
论文阅读
[Jan-20] Seesaw Loss for Long-Tailed Instance Segmentation
论文阅读
[Jan-19] Equalization Loss for Long-Tailed Object Recognition
论文阅读
[Jan-18] Class-Balanced Loss Based on Effective Number of Samples
论文阅读
[Jan-17] Decoupling Representation and Classifier for Long-Tailed Recognition
论文阅读
[Jan-16] ELECTRA: Pre-training Text Encoders as Discriminators Rather Than Generators
论文阅读
[Jan-15] ACNet: Strengthening the Kernel Skeletons for Powerful CNN via Asymmetric Convolution Blocks
论文阅读
[Jan-14] ALBERT: A Lite BERT for Self-supervised Learning of Language Representations
论文阅读
[Jan-13] Keep it SMPL: Automatic Estimation of 3D Human Pose and Shape from a Single Image
Python
[Jan-12] 使用json库进行OpenPose输出关节点转换(25→18)
论文阅读
[Jan-11] Language Models are Unsupervised Multitask Learners
论文阅读
[Jan-10] mT5: A massively multilingual pre-trained text-to-text transformer
论文阅读
[Jan-9] GLU Variants Improve Transformer
论文阅读
[Jan-8] Exploring the Limits of Transfer Learning with a Unified Text-to-Text Transformer
论文阅读
[Jan-7] SMPL: A Skinned Multi-Person Linear Model
论文阅读
[Jan-6] Learning Transferable Visual Models From Natural Language Supervision
论文阅读
[Jan-5] Long-tail learning via logit adjustment
论文阅读
[Jan-4] On the Relationship between Self-Attention and Convolutional Layers
论文阅读
[Jan-3] Improving Language Understanding by Generative Pre-Training
论文阅读
[Jan-2] BERT: Pre-training of Deep Bidirectional Transformers for Language Understanding
论文阅读
[Jan-1] Deep contextualized word representations
Dec-2020
论文阅读
[Dec-31] Deformable DETR: Deformable Transformers for End-to-End Object Detection
论文阅读
[Dec-30] An Image is Worth 16x16 Words: Transformers for Image Recognition at Scale
论文阅读
[Dec-29] Generative Pretraining from Pixels
论文阅读
[Dec-28] Do We Need Zero Training Loss After Achieving Zero Training Error?
论文阅读
[Dec-27] REALM: Retrieval-Augmented Language Model Pre-Training
论文阅读
[Dec-26] OneNet: Towards End-to-End One-Stage Object Detection
论文阅读
[Dec-25] Implicit Gradient Regularization
论文阅读
[Dec-24] Accurate, Large Minibatch SGD: Training ImageNet in 1 Hour
论文阅读
[Dec-23] Multimodal Machine Learning: A Survey and Taxonomy
论文阅读
[Dec-22] Learning Continuous Image Representation with Local Implicit Image Function
论文阅读
[Dec-21] AdaX: Adaptive Gradient Descent with Exponential Long Term Memory
论文阅读
[Dec-20] Adafactor: Adaptive Learning Rates with Sublinear Memory Cost
论文阅读
[Dec-19] Stochastic Gradient Methods with Layer-wise Adaptive Moments for Training of Deep Networks
论文阅读
[Dec-18] Simple Copy-Paste is a Strong Data Augmentation Method for Instance Segmentation
论文阅读
[Dec-17] Large Batch Optimization for Deep Learning: Training BERT in 76 minutes
深度学习
[Dec-16] 卷积神经网络的可视化
论文阅读
[Dec-15] Large Batch Training of Convolutional Networks
论文阅读
[Dec-14] Lookahead Optimizer: k steps forward, 1 step back
论文阅读
[Dec-13] On the Variance of the Adaptive Learning Rate and Beyond
论文阅读
[Dec-12] Incorporating Nesterov Momentum into Adam
Python
[Dec-11] Pytorch中的Hook机制
论文阅读
[Dec-10] On the Convergence of Adam and Beyond
论文阅读
[Dec-9] Adam: A Method for Stochastic Optimization
论文阅读
[Dec-8] On the importance of initialization and momentum in deep learning
论文阅读
[Dec-7] A Direct Adaptive Method for Faster Backpropagation Learning: The RPROP Algorithm
论文阅读
[Dec-6] ADADELTA: An Adaptive Learning Rate Method
论文阅读
[Dec-5] Don’t Decay the Learning Rate, Increase the Batch Size
论文阅读
[Dec-4] InfoVAE: Balancing Learning and Inference in Variational Autoencoders
论文阅读
[Dec-3] Understanding disentangling in β-VAE
论文阅读
[Dec-2] β-VAE: Learning Basic Visual Concepts with a Constrained Variational Framework
论文阅读
[Dec-1] Attentional Feature Fusion
Nov-2020
论文阅读
[Nov-30] Memory-Efficient Adaptive Optimization
论文阅读
[Nov-29] Averaging Weights Leads to Wider Optima and Better Generalization
论文阅读
[Nov-28] Decoupled Weight Decay Regularization
论文阅读
[Nov-27] ULSAM: Ultra-Lightweight Subspace Attention Module for Compact Convolutional Neural Networks
论文阅读
[Nov-25] A^2-Nets: Double Attention Networks
论文阅读
[Nov-24] Neural Architecture Search for Lightweight Non-Local Networks
Python
[Nov-23] 使用Mayavi库进行3D绘图
论文阅读
[Nov-22] Interlaced Sparse Self-Attention for Semantic Segmentation
深度学习
[Nov-21] 卷积神经网络中的自注意力机制(Self-Attention Mechanism)
论文阅读
[Nov-20] Through-Wall Human Mesh Recovery Using Radio Signals
论文阅读
[Nov-19] A simple yet effective baseline for 3d human pose estimation
深度学习
[Nov-18] 卷积神经网络中的注意力机制(Attention Mechanism)
论文阅读
[Nov-17] Monocular Human Pose Estimation: A Survey of Deep Learning-based Methods
Python
[Nov-16] 为RTX3090配置深度学习环境
论文阅读
[Nov-15] Asymmetric Non-local Neural Networks for Semantic Segmentation
论文阅读
[Nov-14] Expectation-Maximization Attention Networks for Semantic Segmentation
论文阅读
[Nov-13] Dual Attention Network for Scene Segmentation
Python
[Nov-12] Pytorch构建自己的数据集
论文阅读
[Nov-11] Generating Diverse High-Fidelity Images with VQ-VAE-2
论文阅读
[Nov-10] Neural Discrete Representation Learning
论文阅读
[Nov-8] CCNet: Criss-Cross Attention for Semantic Segmentation
论文阅读
[Nov-7] GCNet: Non-local Networks Meet Squeeze-Excitation Networks and Beyond
论文阅读
[Nov-6] Non-Local Neural Networks
论文阅读
[Nov-5] Through-Wall Human Pose Estimation Using Radio Signals
论文阅读
[Nov-4] Competitive Inner-Imaging Squeeze and Excitation for Residual Network
论文阅读
[Nov-3] SRM: A Style-based Recalibration Module for Convolutional Neural Networks
论文阅读
[Nov-2] Tiled Squeeze-and-Excite: Channel Attention With Local Spatial Context
论文阅读
[Nov-1] An Attention Module for Convolutional Neural Networks
Oct-2020
论文阅读
[Oct-31] NAM: Normalization-based Attention Module
论文阅读
[Oct-30] Residual Attention Network for Image Classification
论文阅读
[Oct-29] Attention as Activation
论文阅读
[Oct-28] Interflow: Aggregating Multi-layer Feature Mappings with Attention Mechanism
论文阅读
[Oct-27] Spanet: Spatial Pyramid Attention Network for Enhanced Image Recognition
深度学习
[Oct-26] 音乐生成
论文阅读
[Oct-25] EPSANet: An Efficient Pyramid Split Attention Block on Convolutional Neural Network
论文阅读
[Oct-24] End-to-End Adversarial Text-to-Speech
论文阅读
[Oct-23] Unsupervised Anomaly Detection with Generative Adversarial Networks to Guide Marker Discovery
论文阅读
[Oct-22] BA^2M: A Batch Aware Attention Module for Image Classification
Python
[Oct-21] 使用tifffile库处理tiff格式图像
论文阅读
[Oct-20] Weight Excitation: Built-in Attention Mechanisms in Convolutional Neural Networks
论文阅读
[Oct-19] Weighted Channel Dropout for Regularization of Deep Convolutional Neural Network
论文阅读
[Oct-18] DIANet: Dense-and-Implicit Attention Network
论文阅读
[Oct-17] On the Measure of Intelligence
Python
[Oct-16] (目标检测适用)批量修改xml文件中的name字段
论文阅读
[Oct-15] DCANet: Learning Connected Attentions for Convolutional Neural Networks
论文阅读
[Oct-14] Rotate to Attend: Convolutional Triplet Attention Module
论文阅读
[Oct-13] Improving Convolutional Networks with Self-calibrated Convolutions
论文阅读
[Oct-12] You Only Look Twice: Rapid Multi-Scale Object Detection In Satellite Imagery
论文阅读
[Oct-11] The Hardware Lottery
论文阅读
[Oct-10] Gather-Excite: Exploiting Feature Context in Convolutional Neural Networks
论文阅读
[Oct-9] FcaNet: Frequency Channel Attention Networks
论文阅读
[Oct-8] Spatial Group-wise Enhance: Improving Semantic Feature Learning in Convolutional Networks
论文阅读
[Oct-7] ECA-Net: Efficient Channel Attention for Deep Convolutional Neural Networks
论文阅读
[Oct-6] Concurrent Spatial and Channel Squeeze & Excitation in Fully Convolutional Networks
论文阅读
[Oct-5] CBAM: Convolutional Block Attention Module
论文阅读
[Oct-4] BAM: Bottleneck Attention Module
论文阅读
[Oct-3] Global Second-order Pooling Convolutional Networks
论文阅读
[Oct-2] Selective Kernel Networks
论文阅读
[Oct-1] Squeeze-and-Excitation Networks
Sep-2020
论文阅读
[Sep-30] Self-Orthogonality Module: A Network Architecture Plug-in for Learning Orthogonal Filters
论文阅读
[Sep-29] Raise a Child in Large Language Model: Towards Effective and Generalizable Fine-tuning
论文阅读
[Sep-28] Why gradient clipping accelerates training: A theoretical justification for adaptivity
论文阅读
[Sep-27] Variational Discriminator Bottleneck: Improving Imitation Learning, Inverse RL, and GANs by Constraining Information Flow
论文阅读
[Sep-26] AdderNet: Do We Really Need Multiplications in Deep Learning?
Python
[Sep-25] 使用Matplotlib绘制训练曲线
论文阅读
[Sep-24] Deep Variational Information Bottleneck
论文阅读
[Sep-23] Virtual Adversarial Training: A Regularization Method for Supervised and Semi-Supervised Learning
论文阅读
[Sep-22] Improve Generalization and Robustness of Neural Networks via Weight Scale Shifting Invariant Regularizations
论文阅读
[Sep-21] The Geometric Occam’s Razor Implicit in Deep Learning
论文阅读
[Sep-20] Implicit Gradient Regularization
论文阅读
[Sep-19] Spectral Norm Regularization for Improving the Generalizability of Deep Learning
论文阅读
[Sep-18] Understanding the Role of Individual Units in a Deep Neural Network
论文阅读
[Sep-17] High Frequency Component Helps Explain the Generalization of Convolutional Neural Networks
Python
[Sep-16] ECCV 2020 Tutorial：PyTorch性能调优指南
论文阅读
[Sep-15] Rethinking Pre-training and Self-training
论文阅读
[Sep-14] Rethinking ImageNet Pre-training
Python
[Sep-13] 使用tqdm库绘制进度条
论文阅读
[Sep-12] Unsupervised Translation of Programming Languages
Python
[Sep-11] 使用numpy.bincount计算混淆矩阵
论文阅读
[Sep-10] Neural Architecture Search without Training
论文阅读
[Sep-9] ResNeSt: Split-Attention Networks
论文阅读
[Sep-8] Deep Laplacian Pyramid Networks for Fast and Accurate Super-Resolution
论文阅读
[Sep-7] Selective Kernel Networks
论文阅读
[Sep-6] DropBlock: A regularization method for convolutional networks
论文阅读
[Sep-5] Funnel Activation for Visual Recognition
论文阅读
[Sep-4] Learning in the Frequency Domain
论文阅读
[Sep-3] Simple Regret Minimization for Contextual Bandits
机器学习
[Sep-2] Multi-Armed Bandit(MAB)：多臂老虎机
Python
[Sep-1] 批量处理文件夹内的图片
Aug-2020
论文阅读
[Aug-31] Learning Sparse Neural Networks through L0 Regularization
深度学习
[Aug-27] 图像超分辨率(Super Resolution)
随笔
[Aug-18] 讨论带传动的拉力关系
论文阅读
[Aug-17] Closed-loop Matters: Dual Regression Networks for Single Image Super-Resolution
数学
[Aug-16] 适定(well-posed)问题与不适定(ill-posed)问题
随笔
[Aug-15] 立方体电阻的等效问题
随笔
[Aug-14] 存储文件会增加手机的质量吗？
随笔
[Aug-13] 彩虹的尽头是什么？
论文阅读
[Aug-12] ESRGAN: Enhanced Super-Resolution Generative Adversarial Networks
论文阅读
[Aug-11] Real-Time Single Image and Video Super-Resolution Using an Efficient Sub-Pixel Convolutional Neural Network
论文阅读
[Aug-10] Photo-Realistic Single Image Super-Resolution Using a Generative Adversarial Network
论文阅读
[Aug-9] Second-order Attention Network for Single Image Super-Resolution
论文阅读
[Aug-8] Big Bird: Transformers for Longer Sequences
论文阅读
[Aug-7] Self-training with Noisy Student improves ImageNet classification
论文阅读
[Aug-6] Enhanced Deep Residual Networks for Single Image Super-Resolution
论文阅读
[Aug-5] Accurate Image Super-Resolution Using Very Deep Convolutional Networks
论文阅读
[Aug-4] Accelerating the Super-Resolution Convolutional Neural Network
论文阅读
[Aug-3] Image Super-Resolution Using Deep Convolutional Networks
论文阅读
[Aug-2] Deep Back-Projection Networks For Super-Resolution
论文阅读
[Aug-1] Image Super-Resolution Using Very Deep Residual Channel Attention Networks
Jul-2020
深度学习
[Jul-26] 对抗训练(Adversarial Training)：攻击和防御
论文阅读
[Jul-20] CornerNet: Detecting Objects as Paired Keypoints
论文阅读
[Jul-18] Movement Pruning: Adaptive Sparsity by Fine-Tuning
论文阅读
[Jul-15] SCAN: Learning to Classify Images without Labels
论文阅读
[Jul-14] Synthesizer: Rethinking Self-Attention in Transformer Models
论文阅读
[Jul-13] Language Models are Few-Shot Learners
论文阅读
[Jul-12] Deep Ensembles: A Loss Landscape Perspective
论文阅读
[Jul-11] When BERT Plays the Lottery, All Tickets Are Winning
论文阅读
[Jul-10] Deep image reconstruction from human brain activity
论文阅读
[Jul-9] Investigating Human Priors for Playing Video Games
论文阅读
[Jul-8] Meta-Learning with Implicit Gradients
论文阅读
[Jul-7] A critical analysis of self-supervision, or what we can learn from a single image
论文阅读
[Jul-6] Faster Neural Network Training with Data Echoing
论文阅读
[Jul-5] Concept Learning with Energy-Based Models
论文阅读
[Jul-4] Big Transfer (BiT): General Visual Representation Learning
论文阅读
[Jul-3] Divide-and-Conquer Monte Carlo Tree Search For Goal-Directed Planning
论文阅读
[Jul-2] Reinforcement Learning with Augmented Data
论文阅读
[Jul-1] TAPAS: Weakly Supervised Table Parsing via Pre-training
Jun-2020
论文阅读
[Jun-30] Jukebox: A Generative Model for Music
论文阅读
[Jun-29] Do ImageNet Classifiers Generalize to ImageNet?
论文阅读
[Jun-28] Group Normalization
论文阅读
[Jun-27] Weight Standardization
论文阅读
[Jun-26] mixup: Beyond Empirical Risk Minimization
论文阅读
[Jun-20] DETR：End-to-End Object Detection with Transformers
数学
[Jun-17] 张量分解(Tensor Decomposition)
论文阅读
[Jun-13] YOLOv4: Optimal Speed and Accuracy of Object Detection
深度学习
[Jun-11] 连接时序分类
英语
[Jun-2] 英语构词法
英语
[Jun-1] 英语国际音标
May-2020
深度学习
[May-31] 人体姿态估计(Human Pose Estimation)
机器学习
[May-29] Gaussian Mixture Model(GMM)：高斯混合模型
游记
[May-28] （英国篇）伯克郡：温莎古堡探险记
游记
[May-27] （英国篇）格林尼治：计时与经度之始
游记
[May-26] （英国篇）牛津郡：学府与古迹
游记
[May-25] （英国篇）剑桥郡：不带走一片云彩
游记
[May-24] （英国篇）伦敦：拨开浓雾，但见日落
深度学习
[May-23] 图像到图像翻译(Image-to-Image Translation)
机器学习
[May-22] Transfer Learning：迁移学习
机器学习
[May-21] Lifelong Learning：终身学习
机器学习
[May-20] Meta Learning：元学习
机器学习
[May-19] Anomaly Detection：异常检测
论文阅读
[May-17] Recent Advances in Deep Learning for Object Detection
深度学习
[May-16] 阅读理解
深度学习
[May-15] 文本检测与识别(Text Detection and Recognition)
深度学习
[May-14] 图像描述
深度学习
[May-13] 文本摘要
深度学习
[May-12] 行人检测与属性识别(Pedestrian Detection and Attribute Recognition)
深度学习
[May-10] 人脸检测, 识别与验证(Face Detection, Recognition, and Verification)
论文阅读
[May-9] DeepFace: Closing the Gap to Human-Level Performance in Face Verification
深度学习
[May-8] 目标检测(Object Detection)
深度学习
[May-7] 图像分割(Image Segmentation)
深度学习
[May-6] 图像识别(Image Recognition)
机器学习
[May-5] Mean-Shift
机器学习
[May-4] 谱聚类(Spectral Clustering)
机器学习
[May-3] 层次聚类
机器学习
[May-2] K-Means聚类
深度学习
[May-1] 网络压缩
Apr-2020
深度学习
[Apr-30] 混合精度训练(Mixed Precision Training)
深度学习
[Apr-29] 词嵌入
深度学习
[Apr-28] 深度学习的可解释性
深度学习
[Apr-27] 预训练语言模型(Pretrained Language Model)
深度学习
[Apr-25] Transformer
深度学习
[Apr-24] 自注意力机制(Self-Attention Mechanism)
深度学习
[Apr-23] 记忆增强神经网络(Memory Augmented Neural Network)
深度学习
[Apr-22] 序列到序列模型中的注意力机制(Attention Mechanism)
深度学习
[Apr-21] 序列到序列模型(Sequence to sequence)
深度学习
[Apr-20] 胶囊网络
论文阅读
[Apr-19] Convolutional Neural Networks for Sentence Classification
机器学习
[Apr-18] Radial Basis Function(RBF)：径向基函数网络
机器学习
[Apr-17] 前馈神经网络
机器学习
[Apr-16] Deep Belief Network：深度信念网络
机器学习
[Apr-15] Restricted Boltzmann Machine：受限玻尔兹曼机
机器学习
[Apr-14] Boltzmann Machine：玻尔兹曼机
机器学习
[Apr-13] Hopfield Neural Network：Hopfield神经网络
机器学习
[Apr-12] Energy-based Model：能量模型
机器学习
[Apr-11] 主成分分析(Principal Component Analysis, PCA)
机器学习
[Apr-9] Autoencoder: 自编码器
机器学习
[Apr-8] 稀疏编码(Sparse Coding)
机器学习
[Apr-7] 流形学习
机器学习
[Apr-5] 偏最小二乘回归(Partial Least Squares, PLS)
机器学习
[Apr-4] 前向逐步回归(Stagewise Regression)
论文阅读
[Apr-3] MMDetection: Open MMLab Detection Toolbox and Benchmark
Python
[Apr-2] 处理Matlab中的mat格式文件
Python
[Apr-1] LeetCode刷题指南(Python)
Mar-2020
机器学习
[Mar-31] 局部加权线性回归(Local Weighted Linear Regression)
机器学习
[Mar-30] 岭回归与LASSO回归(Ridge/LASSO Regression)
机器学习
[Mar-29] Tube回归(Tube Regression)
机器学习
[Mar-28] 朴素贝叶斯(Naive Bayes)
机器学习
[Mar-27] Recommender System：推荐系统
机器学习
[Mar-26] 期望最大算法(Expectation Maximization, EM)
机器学习
[Mar-25] 变分推断(Variational Inference)
机器学习
[Mar-24] 线性判别分析(Linear Discriminant Analysis, LDA)
机器学习
[Mar-23] k近邻算法(k-Nearest Neighbor, kNN)
机器学习
[Mar-22] 提升树(Boosting Tree)
机器学习
[Mar-21] 梯度提升决策树(Gradient Boosted Decision Tree, GBDT)
机器学习
[Mar-20] 随机森林(Random Forest)
机器学习
[Mar-19] 决策树(Decision Tree)
机器学习
[Mar-18] 集成学习中的提升(Boosting)方法
机器学习
[Mar-17] 集成学习中的Bagging(Bootstrap Aggregation)方法
机器学习
[Mar-16] 集成学习中的组合(Blending)策略
机器学习
[Mar-15] 支持向量回归(Support Vector Regression, SVR)
机器学习
[Mar-14] 支持向量机(Support Vector Machine, SVM)
机器学习
[Mar-13] 逻辑回归(Logistic Regression)
机器学习
[Mar-12] 线性回归(Linear Regression)
机器学习
[Mar-11] 感知机(Perceptron)
深度学习
[Mar-9] 图神经网络(Graph Neural Network)
深度学习
[Mar-8] 递归神经网络(Recursive Neural Network)
深度学习
[Mar-7] 循环神经网络(Recurrent Neural Network)
深度学习
[Mar-6] 卷积神经网络(Convolutional Neural Network)
深度学习
[Mar-5] 深度学习中的初始化方法(Initialization)
深度学习
[Mar-4] 深度学习中的归一化方法(Normalization)
深度学习
[Mar-3] 深度学习中的正则化方法(Regularization)
深度学习
[Mar-2] 深度学习中的优化算法(Optimization)
深度学习
[Mar-1] 深度学习中的激活函数(Activation Function)
Feb-2020
Python
[Feb-29] 数据结构与算法(Python)
机器学习
[Feb-7] 分类任务的常用性能指标
机器学习
[Feb-6] 模型评估方法
机器学习
[Feb-5] 模型复杂度理论
机器学习
[Feb-4] 机器学习的一些定理
数学
[Feb-3] 概率分布之间的散度(Divergence)
数学
[Feb-2] 参数估计(Parameter Estimation)
[Feb-1] 云游戏编年史
数学
[Feb-1] 抽样分布(Sampling Distribution)
Jan-2020
论文阅读
[Jan-29] Bag of Tricks for Image Classification with Convolutional Neural Networks
随笔
[Jan-27] “飞蛾扑火”问题研究
Python
[Jan-24] Python用户笔记
英语
[Jan-20] 英语简史
数学
[Jan-10] 数理统计学(Mathematic Statistics)的基本概念
深度学习
[Jan-2] 深度学习(Deep Learning)概述
机器学习
[Jan-1] 机器学习(Machine Learning)概述