【导读】图像分类作为计算机视觉的经典任务。一直被学者们研究探讨,本文介绍并比较了2014年以来较为出色的图像分类论文与代码 性能比较 为了简单,只列出在ImageNet上Top1 和 Top5 精度比较,准确度越高并不代表模型越好,因为一些网络是为了减小模型复杂度设计的。 论文与代码 VGGVery Deep Convolutional Networks for Large-Scale Image Recognition. Karen Simonyan, Andrew Zisserman pdf: https:///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.py
GoogleNetGoing Deeper with Convolutions Christian Szegedy, Wei Liu, Yangqing Jia, Pierre Sermanet, Scott Reed, Dragomir Anguelov, Dumitru Erhan, Vincent Vanhoucke, Andrew Rabinovich pdf: https:///abs/1409.4842 code: unofficial-tensorflow : https://github.com/conan7882/GoogLeNet-Inception code: unofficial-caffe : https://github.com/lim0606/caffe-googlenet-bn
PReLU-netsDelving Deep into Rectifiers: Surpassing Human-Level Performance on ImageNet Classification Kaiming He, Xiangyu Zhang, Shaoqing Ren, Jian Sun ResNetDeep Residual Learning for Image Recognition Kaiming He, Xiangyu Zhang, Shaoqing Ren, Jian Sun pdf: https:///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-resnet
PreActResNetIdentity Mappings in Deep Residual Networks Kaiming He, Xiangyu Zhang, Shaoqing Ren, Jian Sun pdf: https:///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
Inceptionv3Rethinking the Inception Architecture for Computer Vision Christian Szegedy, Vincent Vanhoucke, Sergey Ioffe, Jonathon Shlens, Zbigniew Wojna pdf: https:///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
Inceptionv4 && Inception-ResNetv2Inception-v4, Inception-ResNet and the Impact of Residual Connections on Learning Christian Szegedy, Sergey Ioffe, Vincent Vanhoucke, Alex Alemi pdf: https:///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-v2
RiRResnet in Resnet: Generalizing Residual Architectures Sasha Targ, Diogo Almeida, Kevin Lyman pdf: https:///abs/1603.08029 code: unofficial-tensorflow : https://github.com/SunnerLi/RiR-Tensorflow code: unofficial-chainer : https://github.com/nutszebra/resnet_in_resnet
Stochastic Depth ResNetDeep Networks with Stochastic Depth Gao Huang, Yu Sun, Zhuang Liu, Daniel Sedra, Kilian Weinberger pdf: https:///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_keras
WRNWide Residual Networks Sergey Zagoruyko, Nikos Komodakis pdf: https:///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.pytorch
squeezenetSqueezeNet: 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:///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-Residual
GeNetGenetic CNN Lingxi Xie, Alan Yuille MetaQNNDesigning Neural Network Architectures using Reinforcement Learning Bowen Baker, Otkrist Gupta, Nikhil Naik, Ramesh Raskar PyramidNetDeep Pyramidal Residual Networks Dongyoon Han, Jiwhan Kim, Junmo Kim pdf: https:///abs/1610.02915 code: official : https://github.com/jhkim89/PyramidNet code: unofficial-pytorch : https://github.com/dyhan0920/PyramidNet-PyTorch
DenseNetDensely Connected Convolutional Networks Gao Huang, Zhuang Liu, Laurens van der Maaten, Kilian Q. Weinberger pdf: https:///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-Keras
FractalNetFractalNet: Ultra-Deep Neural Networks without Residuals Gustav Larsson, Michael Maire, Gregory Shakhnarovich pdf: https:///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/FractalNet
ResNextAggregated Residual Transformations for Deep Neural Networks Saining Xie, Ross Girshick, Piotr Dollár, Zhuowen Tu, Kaiming He pdf: https:///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-tensorflow
IGCV1Interleaved Group Convolutions for Deep Neural Networks Ting Zhang, Guo-Jun Qi, Bin Xiao, Jingdong Wang Residual Attention NetworkResidual Attention Network for Image Classification Fei Wang, Mengqing Jiang, Chen Qian, Shuo Yang, Cheng Li, Honggang Zhang, Xiaogang Wang, Xiaoou Tang pdf: https:///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-network
XceptionXception: Deep Learning with Depthwise Separable Convolutions François Chollet pdf: https:///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.py
MobileNetMobileNets: 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:///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.py
PolyNetPolyNet: A Pursuit of Structural Diversity in Very Deep Networks Xingcheng Zhang, Zhizhong Li, Chen Change Loy, Dahua Lin DPNDual Path Networks Yunpeng Chen, Jianan Li, Huaxin Xiao, Xiaojie Jin, Shuicheng Yan, Jiashi Feng pdf: https:///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-pretrained
Block-QNNPractical Block-wise Neural Network Architecture Generation Zhao Zhong, Junjie Yan, Wei Wu, Jing Shao, Cheng-Lin Liu CRU-NetSharing Residual Units Through Collective Tensor Factorization in Deep Neural Networks Chen Yunpeng, Jin Xiaojie, Kang Bingyi, Feng Jiashi, Yan Shuicheng pdfhttps:///abs/1703.02180 code official : https://github.com/cypw/CRU-Net code unofficial-mxnet : https://github.com/bruinxiong/Modified-CRUNet-and-Residual-Attention-Network.mxnet
ShuffleNetShuffleNet: An Extremely Efficient Convolutional Neural Network for Mobile Devices Xiangyu Zhang, Xinyu Zhou, Mengxiao Lin, Jian Sun pdf: https:///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-shufflenet
CondenseNetCondenseNet An Efficient DenseNet using Learned Group Convolutions Gao Huang, Shichen Liu, Laurens van der Maaten, Kilian Q. Weinberger pdf: https:///abs/1711.09224 code: official : https://github.com/ShichenLiu/CondenseNet code: unofficial-tensorflow : https://github.com/markdtw/condensenet-tensorflow
NasNetLearning Transferable Architectures for Scalable Image Recognition Barret Zoph, Vijay Vasudevan, Jonathon Shlens, Quoc V. Le pdf: https:///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-tensorflow
MobileNetV2MobileNetV2: Inverted Residuals and Linear Bottlenecks Mark Sandler, Andrew Howard, Menglong Zhu, Andrey Zhmoginov, Liang-Chieh Chen pdf: https:///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/MobileNetV2
IGCV2IGCV2: Interleaved Structured Sparse Convolutional Neural Networks Guotian Xie, Jingdong Wang, Ting Zhang, Jianhuang Lai, Richang Hong, Guo-Jun Qi hierHierarchical Representations for Efficient Architecture Search Hanxiao Liu, Karen Simonyan, Oriol Vinyals, Chrisantha Fernando, Koray Kavukcuoglu PNasNetProgressive 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:///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.TF
AmoebaNetRegularized Evolution for Image Classifier Architecture Search Esteban Real, Alok Aggarwal, Yanping Huang, Quoc V Le SENetSqueeze-and-Excitation Networks Jie Hu, Li Shen, Samuel Albanie, Gang Sun, Enhua Wu pdf: https:///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.mxnet
ShuffleNetV2ShuffleNet V2: Practical Guidelines for Efficient CNN Architecture Design Ningning Ma, Xiangyu Zhang, Hai-Tao Zheng, Jian Sun pdf: https:///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.Caffe2
IGCV3IGCV3: Interleaved Low-Rank Group Convolutions for Efficient Deep Neural Networks Ke Sun, Mingjie Li, Dong Liu, Jingdong Wang pdf: https:///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/IGCV3
MNasNetMnasNet: Platform-Aware Neural Architecture Search for Mobile Mingxing Tan, Bo Chen, Ruoming Pang, Vijay Vasudevan, Quoc V. Le pdf: https:///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
Github 地址: https://github.com/weiaicunzai/awesome-image-classification
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