# Image Processing, Classification, Recognition and Object Detection

## Image Processing
- [2018 IJCAI] **DehazeGAN: When Image Dehazing Meets Differential Programming**, [[paper]](http://www.ijcai.org/proceedings/2018/0172.pdf), [[bibtex]](/Bibtex/DehazeGAN.bib).
- [2018 AAAI] **Towards Perceptual Image Dehazing by Physics-based Disentanglement and Adversarial Training**, [[paper]](https://pdfs.semanticscholar.org/7a73/6b46b37a67a440a29593e261f7c0b63f0ad5.pdf), [[bibtex]](/Bibtex/Towards%20Perceptual%20Image%20Dehazing%20by%20Physics-based%20Disentanglement%20and%20Adversarial%20Training.bib).
- [2021 TIP] **EnlightenGAN: Deep Light Enhancement without Paired Supervision**, [[paper]](https://arxiv.org/pdf/1906.06972.pdf), [[bibtex]](/Bibtex/EnlightenGAN%20-%20Deep%20Light%20Enhancement%20without%20Paired%20Supervision.bib), sources: [[TAMU-VITA/EnlightenGAN]](https://github.com/TAMU-VITA/EnlightenGAN).

## Image Classification and Recognition
- [2012 NIPS] **ImageNet Classification with Deep Convolutional Neural Networks**, _AlexNet_, [[paper]](https://papers.nips.cc/paper/4824-imagenet-classification-with-deep-convolutional-neural-networks.pdf), [[bibtex]](/Bibtex/ImageNet%20Classification%20with%20Deep%20Convolutional%20Neural%20Networks.bib).
- [2014 ArXiv] **Very Deep Convolutional Networks for Large-Scale Image Recognition**, _VGG_, [[paper]](https://arxiv.org/abs/1409.1556.pdf), [[bibtex]](/Bibtex/Very%20Deep%20Convolutional%20Networks%20for%20Large-Scale%20Image%20Recognition.bib).
- [2014 ECCV] **Visualizing and Understanding Convolutional Networks**, [[paper]](https://arxiv.org/abs/1311.2901.pdf), [[bibtex]](/Bibtex/Visualizing%20and%20Understanding%20Convolutional%20Networks.bib).
- [2015 CVPR] **Going Deeper with Convolutions**, _GoogLeNet_, [[paper]](https://arxiv.org/abs/1409.4842.pdf), [[bibtex]](/Bibtex/Going%20Deeper%20with%20Convolutions.bib).
- [2015 ICCV] **Learning Spatiotemporal Features with 3D Convolutional Networks**, [[paper]](https://www.cv-foundation.org/openaccess/content_iccv_2015/papers/Tran_Learning_Spatiotemporal_Features_ICCV_2015_paper.pdf), [[bibtex]](/Bibtex/Learning%20Spatiotemporal%20Features%20with%203D%20Convolutional%20Networks.bib), [[homepage]](http://vlg.cs.dartmouth.edu/c3d/), sources: [[facebook/C3D]](https://github.com/facebook/C3D), [[hx173149/C3D-tensorflow]](https://github.com/hx173149/C3D-tensorflow).
- [2015 ICCV] **Delving Deep into Rectifiers: Surpassing Human-Level Performance on ImageNet Classification**, [[paper]](https://arxiv.org/abs/1502.01852), [[bibtex]](/Bibtex/Delving%20Deep%20into%20Rectifiers.bib), [[Kaiming He's homepage]](http://kaiminghe.com), sources: [[nutszebra/prelu_net]](https://github.com/nutszebra/prelu_net).
- [2015 ICMLW] **Siamese Neural Networks for One-shot Image Recognition**, [[paper]](https://www.cs.cmu.edu/~rsalakhu/papers/oneshot1.pdf), [[bibtex]](/Bibtex/Siamese%20Neural%20Networks%20for%20One-shot%20Image%20Recognition.bib), sources: [[Goldesel23/Siamese-Networks-for-One-Shot-Learning]](https://github.com/Goldesel23/Siamese-Networks-for-One-Shot-Learning).
- [2016 CVPR] **Deep Residual Learning for Image Recognition**, [[paper]](https://arxiv.org/abs/1512.03385), [[bibtex]](/Bibtex/Deep%20Residual%20Learning%20for%20Image%20Recognition.bib), sources: [[wenxinxu/resnet-in-tensorflow]](https://github.com/wenxinxu/resnet-in-tensorflow).
- [2016 NIPS] **Matching Networks for One Shot Learning**, [[paper]](https://papers.nips.cc/paper/2016/file/90e1357833654983612fb05e3ec9148c-Paper.pdf), [[bibtex]](/Bibtex/Matching%20Networks%20for%20One%20Shot%20Learning.bib), source: [[AntreasAntoniou/MatchingNetworks]](https://github.com/AntreasAntoniou/MatchingNetworks), [[BoyuanJiang/matching-networks-pytorch]](https://github.com/BoyuanJiang/matching-networks-pytorch).
- [2017 CVPR] **Densely Connected Convolutional Networks**, [[paper]](https://arxiv.org/abs/1608.06993.pdf), [[bibtex]](/Bibtex/Densely%20Connected%20Convolutional%20Networks.bib) sources: [[liuzhuang13/DenseNet]](https://github.com/liuzhuang13/DenseNet).
- [2017 ICLR] **Adversarially Learned Inference**, [[paper]](https://openreview.net/pdf?id=B1ElR4cgg), [[bibtex]](/Bibtex/Adversarially%20Learned%20Inference.bib), sources: [[IshmaelBelghazi/ALI]](https://github.com/IshmaelBelghazi/ALI), [[otenim/ALI-Keras2]](https://github.com/otenim/ALI-Keras2), [[edgarriba/ali-pytorch]](https://github.com/edgarriba/ali-pytorch).
- [2018 CVPR] **Zero-shot Recognition via Semantic Embeddings and Knowledge Graphs**, [[paper]](https://arxiv.org/pdf/1803.08035.pdf), [[bibtex]](/Bibtex/Zero-shot%20Recognition%20via%20Semantic%20Embeddings%20and%20Knowledge%20Graphs.bib), [[blog]](https://www.cnblogs.com/wangxiaocvpr/p/8682608.html), sources: [[JudyYe/zero-shot-gcn]](https://github.com/JudyYe/zero-shot-gcn).
- [2018 CVPR] **Zero-Shot Visual Recognition using Semantics-Preserving Adversarial Embedding Networks**, [[paper]](http://openaccess.thecvf.com/content_cvpr_2018/papers/Chen_Zero-Shot_Visual_Recognition_CVPR_2018_paper.pdf), [[bibtex]](/Bibtex/Zero-Shot%20Visual%20Recognition%20using%20Semantics-Preserving.bib), sources: [[zjuchenlong/sp-aen.cvpr18]](https://github.com/zjuchenlong/sp-aen.cvpr18).
- [2018 CVPR] **Squeeze-and-Excitation Networks**, [[paper]](https://zpascal.net/cvpr2018/Hu_Squeeze-and-Excitation_Networks_CVPR_2018_paper.pdf), [[bibtex]](/Bibtex/Squeeze-and-Excitation%20Networks.bib), sources: [[hujie-frank/SENet]](https://github.com/hujie-frank/SENet).
- [2018 ICLR] **Beyond Shared Hierarchies: Deep Multitask Learning Through Soft Layer Ordering**, [[paper]](https://openreview.net/pdf?id=BkXmYfbAZ), [[bibtex]](/Bibtex/Beyond%20Shared%20Hierarchies%20-%20Deep%20Multitask%20Learning%20Through%20Soft%20Layer%20Ordering.bib).
- [2019 ICCV] **S4L: Self-Supervised Semi-Supervised Learning**, [[paper]](https://openaccess.thecvf.com/content_ICCV_2019/papers/Zhai_S4L_Self-Supervised_Semi-Supervised_Learning_ICCV_2019_paper.pdf), [[bibtex]](/Bibtex/S4L%20-%20Self-Supervised%20Semi-Supervised%20Learning.bib), sources: [[google-research/s4l]](https://github.com/google-research/s4l).
- [2019 ICML] **EfficientNet: Rethinking Model Scaling for Convolutional Neural Networks**, [[paper]](http://proceedings.mlr.press/v97/tan19a/tan19a.pdf), [[bibtex]](/Bibtex/EfficientNet%20-%20Rethinking%20Model%20Scaling%20for%20Convolutional%20Neural%20Networks.bib), sources: [[tensorflow/tpu/models/official/efficientnet/]](https://github.com/tensorflow/tpu/tree/master/models/official/efficientnet), [[zsef123/EfficientNets-PyTorch]](https://github.com/zsef123/EfficientNets-PyTorch), [[narumiruna/efficientnet-pytorch]](https://github.com/narumiruna/efficientnet-pytorch), [[titu1994/keras-efficientnets]](https://github.com/titu1994/keras-efficientnets).
- [2019 NeurIPS] **Stand-Alone Self-Attention in Vision Models**, [[paper]](https://papers.nips.cc/paper/2019/file/3416a75f4cea9109507cacd8e2f2aefc-Paper.pdf), [[bibtex]](/Bibtex/Stand-Alone%20Self-Attention%20in%20Vision%20Models.bib), sources: [[leaderj1001/Stand-Alone-Self-Attention]](https://github.com/leaderj1001/Stand-Alone-Self-Attention), [[google-research/standalone_self_attention_in_vision_models]](https://github.com/google-research/google-research/tree/master/standalone_self_attention_in_vision_models).
- [2020 CVPR] **DeepEMD: Few-Shot Image Classification with Differentiable Earth Movers**, [[paper]](https://openaccess.thecvf.com/content_CVPR_2020/papers/Zhang_DeepEMD_Few-Shot_Image_Classification_With_Differentiable_Earth_Movers_Distance_and_CVPR_2020_paper.pdf), [[bibtex]](/Bibtex/DeepEMD.bib), sources: [[icoz69/DeepEMD]](https://github.com/icoz69/DeepEMD).
- [2020 ArXiv] **ResNeSt: Split-Attention Networks**, [[paper]](https://arxiv.org/pdf/2004.08955.pdf), [[bibtex]](/Bibtex/ResNeSt%20-%20Split-Attention%20Networks.bib), sources: [[zhanghang1989/ResNeSt]](https://github.com/zhanghang1989/ResNeSt).
- [2021 CVPR] **Counterfactual Zero-Shot and Open-Set Visual Recognition**, [[paper]](https://arxiv.org/pdf/2103.00887.pdf), [[bibtex]](/Bibtex/Counterfactual%20Zero-Shot%20and%20Open-Set%20Visual%20Recognition.bib), sources: [[yue-zhongqi/gcm-cf]](https://github.com/yue-zhongqi/gcm-cf).