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.
Contributions welcome! Read the contribution guidelines first. Thank you for lot of attention.
Year
Name
Arxiv
CODE
1998
LeNet : Gradient-based learning applied to document recognition
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2012
AlexNet : ImageNet Classification with Deep Convolutional Neural Networks
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2014
VGGNet : Very Deep Convolutional Networks for Large-Scale Image Recognition
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2015
GoogLeNet : Going Deeper with Convolutions
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2015
InceptionNet : Going deeper with convolutions
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2016
ResNet : Deep Residual Learning for Image Recognition
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2017
SqueezeNet : AlexNet-level accuracy with 50x fewer parameters and <0.5MB model size
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2017
DenseNet : Densely Connected Convolutional Networks
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2017
XceptionNet : Deep Learning with Depthwise Separable Convolutions
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2018
MobileNetV1 : Efficient Convolutional Neural Networks for Mobile Vision Application
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2018
ShuffleNet : An Extremely Efficient Convolutional Neural Network for Mobile Devices
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2018
MobileNetV2 : Inverted Residuals and Linear Bottlenecks
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2018
NASNet : Learning Transferable Architectures for Scalable Image Recognition
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2018
Squeeze Excitation Network : Squeeze-and-Excitation Networks
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2018
Residual Attention Network : Residual Attention Network for Image Classification
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2018
Relative Position Attention : Self-Attention with Relative Position Representations
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2019
CBAM : Convolutional Block Attention Module
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2021
EfficientNet : Rethinking Model Scaling for Convolutional Neural Networks
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2021
Vision Transformer : An Image is Worth 16x16 Words: Transformers for Image Recognition at Scale
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2021
Deit : Training data-efficient image transformers & distillation through attention
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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
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2021
Swin Transformer : Hierarchical Vision Transformer using Shifted Windows
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2022
ConvNeXt : A ConvNet for the 2020s
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2023
ConvNeXt V2: Co-designing and Scaling ConvNets with Masked Autoencoders
PDF
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
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2016
YOLOv1 : You Only Look Once: Unified, Real-Time Object Detection
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2016
SSD(Single Shot Detection) : Single Shot MultiBox Detector
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2017
FPN(Feature Pyramids Network) : Feature Pyramid Networks for Object Detection
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2017
RetinaNet : Focal loss for dense object detection
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2017
Mask-RCNN : Mask R-CNN
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2018
YOLOv3 : An Incremental Improvement
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2018
RefineDet : Single-Shot Refinement Neural Network for Object Detection
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2018
M2Det : A Single-Shot Object Detector based on Multi-Level Feature Pyramid Network
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2018
MetaAnchor: Learning to Detect Objects with Customized Anchors
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2019
Mask scoring r-cnn
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2019
FSFA : Feature selective anchor-free module for single-shot object detection
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2019
Scratchdet : Exploring to train single-shot object detectors from scratch
PDF
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
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2015
DeConvNet(Deconvolution Network) : Learning Deconvolution Network for Semantic Segmentation
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2015
U-Net : Convolutional Networks for Biomedical Image Segmentation
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2016
DilatedNet : Multi-Scale Context Aggregation by dilated Convolution
PDF
2016
ENet : A Deep Neural Network Architecture for Real-Time Semantic Segmentation
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2017
ICNet : ICNet for Real-Time Semantic Segmentation on High-Resolution Images
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2017
GCN : Large Kernel Matters Improve Semantic Segmentation by Global Convolutional Network
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2017
PSPNet : Pyramid Scene Parsing Network
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2017
LinkNet : Exploiting Encoder Representations for Efficient Semantic Segmentation
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2017
DUC, HUC : Understanding Convolution for Semantic Segmentation
PDF
2017
SegNet : A Deep Convolutional Encoder-Decoder Architecture for Image Segmentation
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2018
ShuffleSeg : Real-Time Semantic Segmentation Network
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2018
AdaptSegNet : Learning to Adapt Structured Output Space for Semantic Segmentation
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2018
R2U-Net : Recurrent Residual Convolutional Neural Network based on U-Net for Medical Image Segmentation
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2018
Attention U-Net : Learning Where to Look for the Pancreas
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2019
MultiResUNet : Rethinking the U-Net architecture for multimodal biomedical image segmentation
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2021
SETR : Rethinking Semantic Segmentation from a Sequence-to-Sequence Perspective with Transformers
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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
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2020
LIO(Look-into-Object) : Self-supervised Structure Modeling for Object Recognition
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2020
PMG(Progressive Multi Granularity) : Fine-Grained Visual Classification via Progressive Multi-Granularity Training of Jigsaw Patches
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2020
PIM(Progressive Image Recognition) : Learning Rich Part Hierarchies With Progressive Attention Networks for Fine-Grained Image Recognition
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2021
CAL(Counterfactual Attention Learning) : Counterfactual Attention Learning for Fine-Grained Visual Categorization and Re-identification
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2021
TransFG : TransFG: A Transformer Architecture for Fine-grained Recognition
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2021
ProtoTrees : Neural Prototype Trees for Interpretable Fine-grained Image Recognition
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2021
RAMS-Trans : Recurrent Attention Multi-scale Transformer for Fine-grained Image Recognition
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2021
FFVT : Feature Fusion Vision Transformer for Fine-Grained Visual Categorization
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2022
PIM(plug in Module) : A Novel Plug-in Module for Fine-Grained Visual Classification
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2022
FeNet : A Spatial Feature-Enhanced Attention Neural Network with High-Order Pooling Representation for Application in Pest and Disease Recognition
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2022
MetaFormer : A Unified Meta Framework for Fine-Grained Recognition
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2022
DCAL : Dual Cross-Attention Learning for Fine-Grained Visual Categorization and Object Re-Identification
PDF
Year
Name
Arxiv
CODE
2014
Neural Turing Machines
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2015
Siamese Neural Networks for One-shot Image Recognition
PDF
2016
Matching Networks for One Shot Learning
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2016
Learning to learn by gradient descent by gradient descent
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2016
One-shot Learning with Memory-Augmented Neural Networks
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2017
A Simple Neural Attentive Meta-Learner
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2017
Meta Networks
PDF
2017
ProtoNet : Prototypical Networks for Few-shot Learning
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2017
RelationNet : Learning to Compare: Relation Network for Few-Shot Learning
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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
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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
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2017
Unsupervised Learning of Visual Representations by Solving Jigsaw Puzzles
PDF
2018
Unsupervised Representation Learning by Predicting Image Rotations
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2019
Revisiting self-supervised visual representation learning
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2019
PIRL: Self-Supervised Learning of Pretext-Invariant Representations
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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
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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
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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
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2022
BEiT: BERT Pre-Training of Image Transformers
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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.
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@article = {
title = {Awesome ComputerVision},
author = {Wongi Park},
url = {https://github.com/kalelpark/Awesome-ComputerVision},
year = {2022},
}