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首页 / 图像分类网络详解

图像分类网络详解

OnekeyAI 2021-08-26
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本文总结了图像分类网络在ImageNet数据集上近些年来的研究进展，包括论文以及代码。注意有些模型里面附带Onekey的模型讲解。


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注意：论文列出了ImageNet的top1和top5精确度。这并不一定意味着一个网络比另一个当acc较高,导致一些网络是专注于降低模型的复杂性,而不是提高准确性,或者一些文件只在ImageNet给单一的实验结果,但别人给模型融合或multicrop结果。

  • 卷积网络:卷积网络的名称

  • Imageet top1 acc: Top1准确率

  • ImageNet top5 acc: Top5准确率

  • 发表于:论文在哪个会议或期刊上发表。

Papers&Codes

VGG

Very Deep Convolutional Networks for Large-Scale Image Recognition. Karen Simonyan, Andrew Zisserman

  • pdf: https://arxiv.org/abs/1409.1556

  • 论文详解：图像分类网络演化-VGG（一）

  • 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

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

  • 论文详解：图像分类网络演化-Inception（二）

  • code: unofficial-tensorflow : https://github.com/conan7882/GoogLeNet-Inception

  • code: unofficial-caffe : https://github.com/lim0606/caffe-googlenet-bn

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_net

ResNet

Deep Residual Learning for Image Recognition Kaiming He, Xiangyu Zhang, Shaoqing Ren, Jian Sun

  • pdf: https://arxiv.org/abs/1512.03385

  • 论文详解：图像分类网络演化-ResNet（三）

  • 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

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

Inceptionv3

Rethinking the Inception Architecture for Computer Vision Christian Szegedy, Vincent Vanhoucke, Sergey Ioffe, Jonathon Shlens, Zbigniew Wojna

  • pdf: https://arxiv.org/abs/1512.00567

  • 论文详解：图像分类网络演化-Inception（二）

  • 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-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

  • 论文详解：图像分类网络演化-Inception（二）

  • 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

RiR

Resnet 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_resnet

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_keras

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.pytorch

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-Residual

GeNet

Genetic CNN Lingxi Xie, Alan Yuille

MetaQNN

Designing Neural Network Architectures using Reinforcement Learning Bowen Baker, Otkrist Gupta, Nikhil Naik, Ramesh Raskar

  • pdf: https://arxiv.org/abs/1611.02167

  • code: official : https://github.com/bowenbaker/metaqnn

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-PyTorch

DenseNet

Densely Connected Convolutional Networks Gao Huang, Zhuang Liu, Laurens van der Maaten, Kilian Q. Weinberger

  • pdf: https://arxiv.org/abs/1608.06993

  • 论文详解：图像分类网络演化-SENet（四）

  • 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

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/FractalNet

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

  • 论文详解：图像分类网络演化-ResNet（三）

  • 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

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/InterleavedGroupConvolutions

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-network

Xception

Xception: Deep Learning with Depthwise Separable Convolutions François Chollet

  • pdf: https://arxiv.org/abs/1610.02357

  • 论文详解：图像分类网络演化-Xception（五）

  • 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

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

  • 论文详解：图像分类网络演化-MobileNet（六）

  • 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

PolyNet

PolyNet: A Pursuit of Structural Diversity in Very Deep Networks Xingcheng Zhang, Zhizhong Li, Chen Change Loy, Dahua Lin

  • pdf: https://arxiv.org/abs/1611.05725

  • code: official : https://github.com/open-mmlab/polynet

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-pretrained

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/1708.05552

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.mxnet

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

  • 论文详解：图像分类网络演化-ShuffleNet（七）

  • 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

CondenseNet

CondenseNet: An Efficient DenseNet using Learned Group Convolutions Gao 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-tensorflow

NasNet

Learning Transferable Architectures for Scalable Image Recognition Barret 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-tensorflow

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

  • 论文详解：图像分类网络演化-MobileNet（六）

  • 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

IGCV2

IGCV2: Interleaved Structured Sparse Convolutional Neural Networks Guotian Xie, Jingdong Wang, Ting Zhang, Jianhuang Lai, Richang Hong, Guo-Jun Qi

  • pdf: https://arxiv.org/abs/1804.06202

hier

Hierarchical Representations for Efficient Architecture Search Hanxiao Liu, Karen Simonyan, Oriol Vinyals, Chrisantha Fernando, Koray Kavukcuoglu

  • pdf: https://arxiv.org/abs/1711.00436

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.TF

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_net

SENet

Squeeze-and-Excitation Networks Jie Hu, Li Shen, Samuel Albanie, Gang Sun, Enhua Wu

  • pdf: https://arxiv.org/abs/1709.01507

  • 论文详解：图像分类网络演化-SENet（四）

  • 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

ShuffleNetV2

ShuffleNet V2: Practical Guidelines for Efficient CNN Architecture Design Ningning Ma, Xiangyu Zhang, Hai-Tao Zheng, Jian Sun

  • pdf: https://arxiv.org/abs/1807.11164

  • 论文详解：图像分类网络演化-ShuffleNet（七）

  • 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

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/IGCV3

MNasNet

MnasNet: Platform-Aware Neural Architecture Search for Mobile Mingxing 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

SKNet

Selective Kernel Networks Xiang Li, Wenhai Wang, Xiaolin Hu, Jian Yang

  • pdf: https://arxiv.org/abs/1903.06586

  • code: official : https://github.com/implus/SKNet

DARTS

DARTS: Differentiable Architecture Search Hanxiao Liu, Karen Simonyan, Yiming Yang

  • pdf: https://arxiv.org/abs/1806.09055

  • code: official : https://github.com/quark0/darts

  • code: unofficial-pytorch : https://github.com/khanrc/pt.darts

  • code: unofficial-tensorflow : https://github.com/NeroLoh/darts-tensorflow

ProxylessNAS

ProxylessNAS: Direct Neural Architecture Search on Target Task and Hardware Han Cai, Ligeng Zhu, Song Han

  • pdf: https://arxiv.org/abs/1812.00332

  • code: official : https://github.com/mit-han-lab/ProxylessNAS

MobileNetV3

Searching for MobileNetV3 Andrew Howard, Mark Sandler, Grace Chu, Liang-Chieh Chen, Bo Chen, Mingxing Tan, Weijun Wang, Yukun Zhu, Ruoming Pang, Vijay Vasudevan, Quoc V. Le, Hartwig Adam

  • pdf: https://arxiv.org/abs/1905.02244

  • 论文详解：图像分类网络演化-MobileNet（六）

  • code: unofficial-pytorch : https://github.com/xiaolai-sqlai/mobilenetv3

  • code: unofficial-pytorch : https://github.com/kuan-wang/pytorch-mobilenet-v3

  • code: unofficial-pytorch : https://github.com/leaderj1001/MobileNetV3-Pytorch

  • code: unofficial-pytorch : https://github.com/d-li14/mobilenetv3.pytorch

  • code: unofficial-caffe : https://github.com/jixing0415/caffe-mobilenet-v3

  • code: unofficial-keras : https://github.com/xiaochus/MobileNetV3

Res2Net

Res2Net: A New Multi-scale Backbone Architecture Shang-Hua Gao, Ming-Ming Cheng, Kai Zhao, Xin-Yu Zhang, Ming-Hsuan Yang, Philip Torr

  • pdf: https://arxiv.org/abs/1904.01169

  • 论文详解：图像分类网络演化-ResNet（三）

  • code: unofficial-pytorch : https://github.com/4uiiurz1/pytorch-res2net

  • code: unofficial-keras : https://github.com/fupiao1998/res2net-keras

EfficientNet

EfficientNet: Rethinking Model Scaling for Convolutional Neural Networks Mingxing Tan, Quoc V. Le

  • pdf: https://arxiv.org/abs/1905.11946

  • code: unofficial-pytorch : https://github.com/lukemelas/EfficientNet-PyTorch

  • code: official-tensorflow : https://github.com/tensorflow/tpu/tree/master/models/official/efficientnet


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