Awesome ComputerVision

This repository is a collection of useful materials for Computer Vision.
The Update will continue, and if you want to be a Contributor, I really appreciate it about send me Pull Request.

Contributing

Contributions welcome! Read the contribution guidelines first. Thank you for lot of attention.

Table of Contents

• Image Classification
• Object Detection
• Semantic Segmentation
• Fine Grained Visual Categorization
• Meta Learning
• Image Self Supervised Learning

Image Classification

Year	Name	Arxiv	CODE
1998	LeNet : Gradient-based learning applied to document recognition	PDF
2012	AlexNet : ImageNet Classification with Deep Convolutional Neural Networks	PDF
2014	VGGNet : Very Deep Convolutional Networks for Large-Scale Image Recognition	PDF
2015	GoogLeNet : Going Deeper with Convolutions	PDF
2015	InceptionNet : Going deeper with convolutions	PDF
2016	ResNet : Deep Residual Learning for Image Recognition	PDF
2017	SqueezeNet : AlexNet-level accuracy with 50x fewer parameters and <0.5MB model size	PDF
2017	DenseNet : Densely Connected Convolutional Networks	PDF
2017	XceptionNet : Deep Learning with Depthwise Separable Convolutions	PDF
2018	MobileNetV1 : Efficient Convolutional Neural Networks for Mobile Vision Application	PDF
2018	ShuffleNet : An Extremely Efficient Convolutional Neural Network for Mobile Devices	PDF
2018	MobileNetV2 : Inverted Residuals and Linear Bottlenecks	PDF
2018	NASNet : Learning Transferable Architectures for Scalable Image Recognition	PDF
2018	Squeeze Excitation Network : Squeeze-and-Excitation Networks	PDF
2018	Residual Attention Network : Residual Attention Network for Image Classification	PDF
2018	Relative Position Attention : Self-Attention with Relative Position Representations	PDF
2019	CBAM : Convolutional Block Attention Module	PDF
2021	EfficientNet : Rethinking Model Scaling for Convolutional Neural Networks	PDF
2021	Vision Transformer : An Image is Worth 16x16 Words: Transformers for Image Recognition at Scale	PDF
2021	Deit : Training data-efficient image transformers & distillation through attention	PDF
2021	PVT : Pyramid Vision Transformer: A Versatile Backbone for Dense Prediction without Convolutions	PDF
2021	T2T : Tokens-to-Token ViT: Training Vision Transformers from Scratch on ImageNet	PDF
2021	DeepVit : DeepViT: Towards Deeper Vision Transformer	PDF
2021	CvT: Introducing Convolutions to Vision Transformers	PDF
2021	CrossViT: Cross-Attention Multi-Scale Vision Transformer for Image Classification	PDF
2021	Focal-T : Focal Attention for Long-Range Interactions in Vision Transformers	PDF
2021	Hybrid Swin Transformers : Efficient large-scale image retrieval with deep feature orthogonality and Hybrid-Swin-Transformers	PDF
2021	Swin Transformer : Hierarchical Vision Transformer using Shifted Windows	PDF
2022	ConvNeXt : A ConvNet for the 2020s	PDF
2023	ConvNeXt V2: Co-designing and Scaling ConvNets with Masked Autoencoders	PDF

Object Detection

Year	Name	Arxiv	CODE
2013	R-CNN : Rich feature hierarchies for accurate object detection and semantic segmentation	PDF
2015	Faster R-CNN : Towards Real-Time Object Detection with Region Proposal Networks	PDF
2016	OHEM : Training Region-based Object Detectors with Online Hard Example Mining	PDF
2016	YOLOv1 : You Only Look Once: Unified, Real-Time Object Detection	PDF
2016	SSD(Single Shot Detection) : Single Shot MultiBox Detector	PDF
2017	FPN(Feature Pyramids Network) : Feature Pyramid Networks for Object Detection	PDF
2017	RetinaNet : Focal loss for dense object detection	PDF
2017	Mask-RCNN : Mask R-CNN	PDF
2018	YOLOv3 : An Incremental Improvement	PDF
2018	RefineDet : Single-Shot Refinement Neural Network for Object Detection	PDF
2018	M2Det : A Single-Shot Object Detector based on Multi-Level Feature Pyramid Network	PDF
2018	MetaAnchor: Learning to Detect Objects with Customized Anchors	PDF
2019	Mask scoring r-cnn	PDF
2019	FSFA : Feature selective anchor-free module for single-shot object detection	PDF
2019	Scratchdet : Exploring to train single-shot object detectors from scratch	PDF

Semantic Segmentation

Year	Name	Arxiv	CODE
2014	DeepLabV1 : Semantic Image Segmentation with Deep Convolutional Nets and Fully Connected CRFs	PDF
2015	FCN(Fully Convolutional Layer) : Fully Convolutional Networks for Semantic Segmentation	PDF
2015	DeConvNet(Deconvolution Network) : Learning Deconvolution Network for Semantic Segmentation	PDF
2015	U-Net : Convolutional Networks for Biomedical Image Segmentation	PDF
2016	DilatedNet : Multi-Scale Context Aggregation by dilated Convolution	PDF
2016	ENet : A Deep Neural Network Architecture for Real-Time Semantic Segmentation	PDF
2017	ICNet : ICNet for Real-Time Semantic Segmentation on High-Resolution Images	PDF
2017	GCN : Large Kernel Matters Improve Semantic Segmentation by Global Convolutional Network	PDF
2017	PSPNet : Pyramid Scene Parsing Network	PDF
2017	LinkNet : Exploiting Encoder Representations for Efficient Semantic Segmentation	PDF
2017	DUC, HUC : Understanding Convolution for Semantic Segmentation	PDF
2017	SegNet : A Deep Convolutional Encoder-Decoder Architecture for Image Segmentation	PDF
2018	ShuffleSeg : Real-Time Semantic Segmentation Network	PDF
2018	AdaptSegNet : Learning to Adapt Structured Output Space for Semantic Segmentation	PDF
2018	R2U-Net : Recurrent Residual Convolutional Neural Network based on U-Net for Medical Image Segmentation	PDF
2018	Attention U-Net : Learning Where to Look for the Pancreas	PDF
2019	MultiResUNet : Rethinking the U-Net architecture for multimodal biomedical image segmentation	PDF
2021	SETR : Rethinking Semantic Segmentation from a Sequence-to-Sequence Perspective with Transformers	PDF
2021	UTNet : A Hybrid Transformer Architecture for Medical Image Segmentation	PDF

Fine Grained Visual Categorization

Year	Name	Arxiv	CODE
2017	MA-CNN : Learning Multi-Attention Convolutional Neural Network for Fine-Grained Image Recognition	PDF
2017	RA-CNN : Recurrent Attention Convolutional Neural Networkfor Fine-grained Image Recognition	PDF
2018	NTS-Net : Learning to Navigate for Fine-grained Classification	PDF
2019	MGE-CNN : Learning a Mixture of Granularity-Specific Experts for Fine-GrainedCategorization	PDF
2019	DCL-Net : Destruction and Construction Learning for Fine-grained Image Recognition	PDF
2020	CIN : Channel Interaction Networks for Fine-Grained Image Categorization	PDF
2020	LIO(Look-into-Object) : Self-supervised Structure Modeling for Object Recognition	PDF
2020	PMG(Progressive Multi Granularity) : Fine-Grained Visual Classification via Progressive Multi-Granularity Training of Jigsaw Patches	PDF
2020	PIM(Progressive Image Recognition) : Learning Rich Part Hierarchies With Progressive Attention Networks for Fine-Grained Image Recognition	PDF
2021	CAL(Counterfactual Attention Learning) : Counterfactual Attention Learning for Fine-Grained Visual Categorization and Re-identification	PDF
2021	TransFG : TransFG: A Transformer Architecture for Fine-grained Recognition	PDF
2021	ProtoTrees : Neural Prototype Trees for Interpretable Fine-grained Image Recognition	PDF
2021	RAMS-Trans : Recurrent Attention Multi-scale Transformer for Fine-grained Image Recognition	PDF
2021	FFVT : Feature Fusion Vision Transformer for Fine-Grained Visual Categorization	PDF
2022	PIM(plug in Module) : A Novel Plug-in Module for Fine-Grained Visual Classification	PDF
2022	FeNet : A Spatial Feature-Enhanced Attention Neural Network with High-Order Pooling Representation for Application in Pest and Disease Recognition	PDF
2022	MetaFormer : A Unified Meta Framework for Fine-Grained Recognition	PDF
2022	DCAL : Dual Cross-Attention Learning for Fine-Grained Visual Categorization and Object Re-Identification	PDF

Meta-Learning

Year	Name	Arxiv	CODE
2014	Neural Turing Machines	PDF
2015	Siamese Neural Networks for One-shot Image Recognition	PDF
2016	Matching Networks for One Shot Learning	PDF
2016	Learning to learn by gradient descent by gradient descent	PDF
2016	One-shot Learning with Memory-Augmented Neural Networks	PDF
2017	A Simple Neural Attentive Meta-Learner	PDF
2017	Meta Networks	PDF
2017	ProtoNet : Prototypical Networks for Few-shot Learning	PDF
2017	RelationNet : Learning to Compare: Relation Network for Few-Shot Learning	PDF
2017	optimization as a model for few-shot learning	PDF
2017	MAML : Model-Agnostic Meta-Learning for Fast Adaptation of Deep Networks	PDF
2017	Meta-SGD: Learning to Learn Quickly for Few-Shot Learning	PDF
2019	R2-D2/LR-D2 : Meta-learning with differentiable closed-form solvers	PDF
2019	MetaOptNet : Meta-Learning with Differentiable Convex Optimization	PDF

Image Self Supervised Learning

Year	Name	Arxiv	CODE
2014	Discriminative Unsupervised Feature Learning with Exemplar Convolutional Neural Networks	PDF
2016	Unsupervised Visual Representation Learning by Context Prediction	PDF
2017	Unsupervised Learning of Visual Representations by Solving Jigsaw Puzzles	PDF
2018	Unsupervised Representation Learning by Predicting Image Rotations	PDF
2019	Revisiting self-supervised visual representation learning	PDF
2019	PIRL: Self-Supervised Learning of Pretext-Invariant Representations	PDF
2020	Momentum Contrast for Unsupervised Visual Representation Learning	PDF
2020	A Simple Framework for Contrastive Learning of Visual Representations	PDF
2020	Big Self-Supervised Models are Strong Semi-Supervised Learners	PDF
2020	MocoV2 : Improved Baselines with Momentum Contrastive Learning	PDF
2020	BYOL : Bootstrap Your Own Latent A New Approach to Self-Supervised Learning	PDF
2020	Simsiam : Exploring Simple Siamese Representation Learning	PDF
2020	Swav : Unsupervised Learning of Visual Features by Contrasting Cluster Assignments	PDF
2021	Barlow twins : Self-Supervised Learning via Redundancy Reduction	PDF
2021	VICReg: Variance-Invariance-Covariance Regularization for Self-Supervised Learning	PDF
2021	Jigsaw Clustering for Unsupervised Visual Representation Learning	PDF
2021	Masked Autoencoders Are Scalable Vision Learners	PDF
2021	SimMIM: A Simple Framework for Masked Image Modeling	PDF
2021	iBOT 🤖: Image BERT Pre-Training with Online Tokenizer	PDF
2022	Tailoring Self-Supervision for Supervised Learning	PDF
2022	BEiT: BERT Pre-Training of Image Transformers	PDF
2023	Denoising Masked AutoEncoders Help Robust Classification	PDF
2023	Designing BERT for Convolutional Networks: Sparse and Hierarchical Masked Modeling	PDF
2023	CIM : Corrupted Image Modeling for Self-Supervised Visual Pre-Training	PDF
2023	PCAE : Progressively Compressed Auto-Encoder for Self-supervised Representation Learning	PDF
2023	HiViT: A Simple and More Efficient Design of Hierarchical Vision Transformer.	PDF

How to cite

@article = {
    title = {Awesome ComputerVision},
    author = {Wongi Park},
    url = {https://github.com/kalelpark/Awesome-ComputerVision},
    year = {2022},
}