重磅!圖像分類相關文獻/代碼大列表 紅色石頭的個人網站:紅色石頭的個人博客-機器學習、深度學習之路?redstonewill.com今天給大家介紹自 2014 年以來,計算機視覺 CV 領域圖像分類方向文獻和代碼的超全總結和列表!總共涉及 36 種 ConvNet 模型。該 GitHub 項目作者是 weiaicunzai,項目地址是:weiaicunzai/awesome-image-classification?github.com 背景 我相信圖像識別是深入到其它機器視覺領域一個很好的起點,特別是對於剛剛入門深度學習的人來說。當我初學 CV 時,犯了很多錯。我當時非常希望有人能告訴我應該從哪一篇論文開始讀起。到目前為止,似乎還沒有一個像 deep-learning-object-detection 這樣的 GitHub 項目。因此,我決定建立一個 GitHub 項目,列出深入學習中關於圖像分類的論文和代碼,以幫助其他人。對於學習路線,我的個人建議是,對於那些剛入門深度學習的人,可以試著從 vgg 開始,然後是 googlenet、resnet,之後可以自由地繼續閱讀列出的其它論文或切換到其它領域。 性能表 基於簡化的目的,我只從論文中列舉出在 ImageNet 上準確率最高的 top1 和 top5。注意,這並不一定意味著準確率越高,一個網路就比另一個網路更好。因為有些網路專註於降低模型複雜性而不是提高準確性,或者有些論文只給出 ImageNet 上的 single crop results,而另一些則給出模型融合或 multicrop results。關於性能表的標註: ConvNet:卷積神經網路的名稱 ImageNet top1 acc:論文中基於 ImageNet 數據集最好的 top1 準確率 ImageNet top5 acc:論文中基於 ImageNet 數據集最好的 top5 準確率 Published In:論文發表在哪個會議或期刊 論文&代碼 1. VGGVery Deep Convolutional Networks for Large-Scale Image Recognition. Karen Simonyan, Andrew Zisserman pdf: https://arxiv.org/abs/1409.1556 code: torchvision : https://github.com/pytorch/vision/blob/master/torchvision/models/vgg.py code: keras-applications : https://github.com/keras-team/keras-applications/blob/master/keras_applications/vgg16.py code: keras-applications : https://github.com/keras-team/keras-applications/blob/master/keras_applications/vgg19.py2. GoogleNet Going Deeper with Convolutions Christian Szegedy, Wei Liu, Yangqing Jia, Pierre Sermanet, Scott Reed, Dragomir Anguelov, Dumitru Erhan, Vincent Vanhoucke, Andrew Rabinovich pdf: https://arxiv.org/abs/1409.4842 code: unofficial-tensorflow : https://github.com/conan7882/GoogLeNet-Inception code: unofficial-caffe : https://github.com/lim0606/caffe-googlenet-bn3. PReLU-nets Delving Deep into Rectifiers: Surpassing Human-Level Performance on ImageNet Classification Kaiming He, Xiangyu Zhang, Shaoqing Ren, Jian Sun pdf: https://arxiv.org/abs/1502.01852 code: unofficial-chainer : https://github.com/nutszebra/prelu_net4. ResNet Deep Residual Learning for Image Recognition Kaiming He, Xiangyu Zhang, Shaoqing Ren, Jian Sun pdf: https://arxiv.org/abs/1512.03385 code: facebook-torch : https://github.com/facebook/fb.resnet.torch code: torchvision : https://github.com/pytorch/vision/blob/master/torchvision/models/resnet.py code: keras-applications : https://github.com/keras-team/keras-applications/blob/master/keras_applications/resnet.py code: unofficial-keras : https://github.com/raghakot/keras-resnet code: unofficial-tensorflow : https://github.com/ry/tensorflow-resnet5. PreActResNet Identity Mappings in Deep Residual Networks Kaiming He, Xiangyu Zhang, Shaoqing Ren, Jian Sun pdf: https://arxiv.org/abs/1603.05027 code: facebook-torch : https://github.com/facebook/fb.resnet.torch/blob/master/models/preresnet.lua code: official : https://github.com/KaimingHe/resnet-1k-layers code: unoffical-pytorch : https://github.com/kuangliu/pytorch-cifar/blob/master/models/preact_resnet.py code: unoffical-mxnet : https://github.com/tornadomeet/ResNet 6. Inceptionv3Rethinking the Inception Architecture for Computer Vision Christian Szegedy, Vincent Vanhoucke, Sergey Ioffe, Jonathon Shlens, Zbigniew Wojna pdf: https://arxiv.org/abs/1512.00567 code: torchvision : https://github.com/pytorch/vision/blob/master/torchvision/models/inception.py code: keras-applications : https://github.com/keras-team/keras-applications/blob/master/keras_applications/inception_v3.py 7. Inceptionv4 && Inception-ResNetv2 Inception-v4, Inception-ResNet and the Impact of Residual Connections on Learning Christian Szegedy, Sergey Ioffe, Vincent Vanhoucke, Alex Alemi pdf: https://arxiv.org/abs/1602.07261 code: unofficial-keras : https://github.com/kentsommer/keras-inceptionV4 code: unofficial-keras : https://github.com/titu1994/Inception-v4 code: unofficial-keras : https://github.com/yuyang-huang/keras-inception-resnet-v28. RIRResnet in Resnet: Generalizing Residual Architectures Sasha Targ, Diogo Almeida, Kevin Lyman pdf: https://arxiv.org/abs/1603.08029 code: unofficial-tensorflow : https://github.com/SunnerLi/RiR-Tensorflow code: unofficial-chainer : https://github.com/nutszebra/resnet_in_resnet9. Stochastic Depth ResNet Deep Networks with Stochastic Depth Gao Huang, Yu Sun, Zhuang Liu, Daniel Sedra, Kilian Weinberger pdf: https://arxiv.org/abs/1603.09382 code: unofficial-torch : https://github.com/yueatsprograms/Stochastic_Depth code: unofficial-chainer : https://github.com/yasunorikudo/chainer-ResDrop code: unofficial-keras : https://github.com/dblN/stochastic_depth_keras10. WRN Wide Residual Networks Sergey Zagoruyko, Nikos Komodakis pdf: https://arxiv.org/abs/1605.07146 code: official : https://github.com/szagoruyko/wide-residual-networks code: unofficial-pytorch : https://github.com/xternalz/WideResNet-pytorch code: unofficial-keras : https://github.com/asmith26/wide_resnets_keras code: unofficial-pytorch : https://github.com/meliketoy/wide-resnet.pytorch11. squeezenet SqueezeNet: AlexNet-level accuracy with 50x fewer parameters and <0.5MB model size Forrest N. Iandola, Song Han, Matthew W. Moskewicz, Khalid Ashraf, William J. Dally, Kurt Keutzer pdf: https://arxiv.org/abs/1602.07360 code: torchvision : https://github.com/pytorch/vision/blob/master/torchvision/models/squeezenet.py code: unofficial-caffe : https://github.com/DeepScale/SqueezeNet code: unofficial-keras : https://github.com/rcmalli/keras-squeezenet code: unofficial-caffe : https://github.com/songhan/SqueezeNet-Residual12. GeNet Genetic CNN Lingxi Xie, Alan Yuille pdf: https://arxiv.org/abs/1703.01513 code: unofficial-tensorflow : https://github.com/aqibsaeed/Genetic-CNN12. MetaQNN Designing Neural Network Architectures using Reinforcement LearningBowen Baker, Otkrist Gupta, Nikhil Naik, Ramesh Raskar pdf: https://arxiv.org/abs/1703.01513 code: official : https://github.com/bowenbaker/metaqnn13. PyramidNet Deep Pyramidal Residual Networks Dongyoon Han, Jiwhan Kim, Junmo Kim pdf: https://arxiv.org/abs/1610.02915 code: official : https://github.com/jhkim89/PyramidNet code: unofficial-pytorch : https://github.com/dyhan0920/PyramidNet-PyTorch14. DenseNet Densely Connected Convolutional Networks Gao Huang, Zhuang Liu, Laurens van der Maaten, Kilian Q. Weinberger pdf: https://arxiv.org/abs/1608.06993 code: official : https://github.com/liuzhuang13/DenseNet code: unofficial-keras : https://github.com/titu1994/DenseNet code: unofficial-caffe : https://github.com/shicai/DenseNet-Caffe code: unofficial-tensorflow : https://github.com/YixuanLi/densenet-tensorflow code: unofficial-pytorch : https://github.com/YixuanLi/densenet-tensorflow code: unofficial-pytorch : https://github.com/bamos/densenet.pytorch code: unofficial-keras : https://github.com/flyyufelix/DenseNet-Keras15. FractalNet FractalNet: Ultra-Deep Neural Networks without Residuals Gustav Larsson, Michael Maire, Gregory Shakhnarovich pdf: https://arxiv.org/abs/1605.07648 code: unofficial-caffe : https://github.com/gustavla/fractalnet code: unofficial-keras : https://github.com/snf/keras-fractalnet code: unofficial-tensorflow : https://github.com/tensorpro/FractalNet16. ResNext Aggregated Residual Transformations for Deep Neural Networks Saining Xie, Ross Girshick, Piotr Dollár, Zhuowen Tu, Kaiming He pdf: https://arxiv.org/abs/1611.05431 code: official : https://github.com/facebookresearch/ResNeXt code: keras-applications : https://github.com/keras-team/keras-applications/blob/master/keras_applications/resnext.py code: unofficial-pytorch : https://github.com/prlz77/ResNeXt.pytorch code: unofficial-keras : https://github.com/titu1994/Keras-ResNeXt code: unofficial-tensorflow : https://github.com/taki0112/ResNeXt-Tensorflow code: unofficial-tensorflow : https://github.com/wenxinxu/ResNeXt-in-tensorflow17. IGCV1 Interleaved Group Convolutions for Deep Neural Networks Ting Zhang, Guo-Jun Qi, Bin Xiao, Jingdong Wang pdf: https://arxiv.org/abs/1707.02725 code official : https://github.com/hellozting/InterleavedGroupConvolutions18. Residual Attention Network Residual Attention Network for Image Classification Fei Wang, Mengqing Jiang, Chen Qian, Shuo Yang, Cheng Li, Honggang Zhang, Xiaogang Wang, Xiaoou Tang pdf: https://arxiv.org/abs/1704.06904 code: official : https://github.com/fwang91/residual-attention-network code: unofficial-pytorch : https://github.com/tengshaofeng/ResidualAttentionNetwork-pytorch code: unofficial-gluon : https://github.com/PistonY/ResidualAttentionNetwork code: unofficial-keras : https://github.com/koichiro11/residual-attention-network19. Xception Xception: Deep Learning with Depthwise Separable ConvolutionsFran?ois Chollet pdf: https://arxiv.org/abs/1610.02357 code: unofficial-pytorch : https://github.com/jfzhang95/pytorch-deeplab-xception/blob/master/modeling/backbone/xception.py code: unofficial-tensorflow : https://github.com/kwotsin/TensorFlow-Xception code: unofficial-caffe : https://github.com/yihui-he/Xception-caffe code: unofficial-pytorch : https://github.com/tstandley/Xception-PyTorch code: keras-applications : https://github.com/keras-team/keras-applications/blob/master/keras_applications/xception.py20. MobileNet MobileNets: Efficient Convolutional Neural Networks for Mobile Vision Applications Andrew G. Howard, Menglong Zhu, Bo Chen, Dmitry Kalenichenko, Weijun Wang, Tobias Weyand, Marco Andreetto, Hartwig Adam pdf: https://arxiv.org/abs/1704.04861 code: unofficial-tensorflow : https://github.com/Zehaos/MobileNet code: unofficial-caffe : https://github.com/shicai/MobileNet-Caffe code: unofficial-pytorch : https://github.com/marvis/pytorch-mobilenet code: keras-applications : https://github.com/keras-team/keras-applications/blob/master/keras_applications/mobilenet.py21. PolyNet PolyNet: A Pursuit of Structural Diversity in Very Deep NetworksXingcheng Zhang, Zhizhong Li, Chen Change Loy, Dahua Lin pdf: https://arxiv.org/abs/1611.05725 code: official : https://github.com/open-mmlab/polynet22. DPN Dual Path Networks Yunpeng Chen, Jianan Li, Huaxin Xiao, Xiaojie Jin, Shuicheng Yan, Jiashi Feng pdf: https://arxiv.org/abs/1707.01629 code: official : https://github.com/cypw/DPNs code: unoffical-keras : https://github.com/titu1994/Keras-DualPathNetworks code: unofficial-pytorch : https://github.com/oyam/pytorch-DPNs code: unofficial-pytorch : https://github.com/rwightman/pytorch-dpn-pretrained23. Block-QNN Practical Block-wise Neural Network Architecture Generation Zhao Zhong, Junjie Yan, Wei Wu, Jing Shao, Cheng-Lin Liu pdf: https://arxiv.org/abs/1708.0555224. CRU-Net Sharing Residual Units Through Collective Tensor Factorization in Deep Neural Networks Chen Yunpeng, Jin Xiaojie, Kang Bingyi, Feng Jiashi, Yan Shuicheng pdf: https://arxiv.org/abs/1703.02180 code official : https://github.com/cypw/CRU-Net code unofficial-mxnet : https://github.com/bruinxiong/Modified-CRUNet-and-Residual-Attention-Network.mxnet25. ShuffleNet ShuffleNet: An Extremely Efficient Convolutional Neural Network for Mobile Devices Xiangyu Zhang, Xinyu Zhou, Mengxiao Lin, Jian Sun pdf: https://arxiv.org/abs/1707.01083 code: unofficial-tensorflow : https://github.com/MG2033/ShuffleNet code: unofficial-pytorch : https://github.com/jaxony/ShuffleNet code: unofficial-caffe : https://github.com/farmingyard/ShuffleNet code: unofficial-keras : https://github.com/scheckmedia/keras-shufflenet26. CondenseNet CondenseNet: An Efficient DenseNet using Learned Group ConvolutionsGao Huang, Shichen Liu, Laurens van der Maaten, Kilian Q. Weinberger pdf: https://arxiv.org/abs/1711.09224 code: official : https://github.com/ShichenLiu/CondenseNet code: unofficial-tensorflow : https://github.com/markdtw/condensenet-tensorflow27. NasNet Learning Transferable Architectures for Scalable Image RecognitionBarret Zoph, Vijay Vasudevan, Jonathon Shlens, Quoc V. Le pdf: https://arxiv.org/abs/1707.07012 code: unofficial-keras : https://github.com/titu1994/Keras-NASNet code: keras-applications : https://github.com/keras-team/keras-applications/blob/master/keras_applications/nasnet.py code: unofficial-pytorch : https://github.com/wandering007/nasnet-pytorch code: unofficial-tensorflow : https://github.com/yeephycho/nasnet-tensorflow28. MobileNetV2 MobileNetV2: Inverted Residuals and Linear Bottlenecks Mark Sandler, Andrew Howard, Menglong Zhu, Andrey Zhmoginov, Liang-Chieh Chen pdf: https://arxiv.org/abs/1801.04381 code: unofficial-keras : https://github.com/xiaochus/MobileNetV2 code: unofficial-pytorch : https://github.com/Randl/MobileNetV2-pytorch code: unofficial-tensorflow : https://github.com/neuleaf/MobileNetV229. IGCV2 IGCV2: Interleaved Structured Sparse Convolutional Neural NetworksGuotian Xie, Jingdong Wang, Ting Zhang, Jianhuang Lai, Richang Hong, Guo-Jun Qi pdf: https://arxiv.org/abs/1804.0620230. hier Hierarchical Representations for Efficient Architecture Search Hanxiao Liu, Karen Simonyan, Oriol Vinyals, Chrisantha Fernando, Koray Kavukcuoglu pdf: https://arxiv.org/abs/1711.0043631. PNasNet Progressive Neural Architecture Search Chenxi Liu, Barret Zoph, Maxim Neumann, Jonathon Shlens, Wei Hua, Li-Jia Li, Li Fei-Fei, Alan Yuille, Jonathan Huang, Kevin Murphy pdf: https://arxiv.org/abs/1712.00559 code: tensorflow-slim : https://github.com/tensorflow/models/blob/master/research/slim/nets/nasnet/pnasnet.py code: unofficial-pytorch : https://github.com/chenxi116/PNASNet.pytorch code: unofficial-tensorflow : https://github.com/chenxi116/PNASNet.TF32. AmoebaNet Regularized Evolution for Image Classifier Architecture Search Esteban Real, Alok Aggarwal, Yanping Huang, Quoc V Le pdf: https://arxiv.org/abs/1802.01548 code: tensorflow-tpu : https://github.com/tensorflow/tpu/tree/master/models/official/amoeba_net33. SENet Squeeze-and-Excitation Networks Jie Hu, Li Shen, Samuel Albanie, Gang Sun, Enhua Wu pdf: https://arxiv.org/abs/1709.01507 code: official : https://github.com/hujie-frank/SENet code: unofficial-pytorch : https://github.com/moskomule/senet.pytorch code: unofficial-tensorflow : https://github.com/taki0112/SENet-Tensorflow code: unofficial-caffe : https://github.com/shicai/SENet-Caffe code: unofficial-mxnet : https://github.com/bruinxiong/SENet.mxnet34. ShuffleNetV2 ShuffleNet V2: Practical Guidelines for Efficient CNN Architecture DesignNingning Ma, Xiangyu Zhang, Hai-Tao Zheng, Jian Sun pdf: https://arxiv.org/abs/1807.11164 code: unofficial-pytorch : https://github.com/Randl/ShuffleNetV2-pytorch code: unofficial-keras : https://github.com/opconty/keras-shufflenetV2 code: unofficial-pytorch : https://github.com/Bugdragon/ShuffleNet_v2_PyTorch code: unofficial-caff2: https://github.com/wolegechu/ShuffleNetV2.Caffe235. IGCV3 IGCV3: Interleaved Low-Rank Group Convolutions for Efficient Deep Neural Networks Ke Sun, Mingjie Li, Dong Liu, Jingdong Wang pdf: https://arxiv.org/abs/1806.00178 code: official : https://github.com/homles11/IGCV3 code: unofficial-pytorch : https://github.com/xxradon/IGCV3-pytorch code: unofficial-tensorflow : https://github.com/ZHANG-SHI-CHANG/IGCV336. MNasNet MnasNet: Platform-Aware Neural Architecture Search for MobileMingxing Tan, Bo Chen, Ruoming Pang, Vijay Vasudevan, Quoc V. Le pdf: https://arxiv.org/abs/1807.11626 code: unofficial-pytorch : https://github.com/AnjieZheng/MnasNet-PyTorch code: unofficial-caffe : https://github.com/LiJianfei06/MnasNet-caffe code: unofficial-MxNet : https://github.com/chinakook/Mnasnet.MXNet code: unofficial-keras : https://github.com/Shathe/MNasNet-Keras-Tensorflow更多 AI 乾貨,請關注公眾號:AI有道(ID:redstonewill) 推薦閱讀: 相關文章 {{#data}} {{title}} {{/data}}