datamonday / CV-Baseline-Papers

Must-Read CV Papers. 计算机视觉必读论文

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Computer Vision Baseline Papers

contributor: datamonday

githubrepo: https://github.com/datamonday/CV-Baseline-Papers


1. 基础论文(Foundation)

模型(Model) 论文名称(Paper) 年份(Year) 被引(cited) 作者(Author) 所属类别(Type) 官方代码(Code) 个人代码(Practice)
AlexNet ImageNet Classification with Deep Convolutional Neural Networks 2012 67950(20/08/20) Alex Krizhevsky,Ilya Sutskever,Geoffrey E. Hinton Classification
ZFNet Visualizing and Understanding Convolutional Networks 2013 9898(20/08/2020) Matthew D. Zeiler,Rob Fergus Classification
VGGNet VERY DEEP CONVOLUTIONAL NETWORKS FOR LARGE-SCALE IMAGE RECOGNITION 2014 42645(20/08/2020) Karen Simonyan,Andrew Zisserman+ Classification
GoogLeNet Going deeper with convolutions 2014 23544(20/08/2020) Christian Szegedy,Wei Liu,Yangqing Jia,et.al Classification
Inception v2 Batch Normalization: Accelerating Deep Network Training by Reducing Internal Covariate Shift 2015 20238(21/08/2020) Sergey Ioffe,Christian Szegedy BN
Inception v3 Rethinking the Inception Architecture for Computer Vision 2015 9190(21/08/2020) Christian Szegedy,Vincent Vanhoucke,Sergey Ioffe,et.al
Inception v4 Inception-v4, Inception-ResNet and the Impact of Residual Connections on Learning 2016 5227(21/08/2020) Christian Szegedy,Sergey Ioffe,Vincent Vanhoucke
ResNet Deep Residual Learning for Image Recognition 2015 52996(25/08/2020) Kaiming He,Xiangyu Zhang,Shaoqing Ren,Jian Sun Classification,Object Detection
ResNeXt Aggregated Residual Transformations for Deep Neural Networks 2017 2715(27/08/2020) Saining Xie,Ross Girshick,et.al Classification,Object Detection
DenseNet Densely Connected Convolutional Networks 2017 10699(27/08/2020) Gao Huang*,Zhuang Liu*,et.al Classification,Object Detection
SENet Squeeze-and-Excitation Networks 2017 3667(27/08/2020) Jie Hu,Li Shen,et.al Classification,Object Detection

2. 图像分类(Image Classification)

模型(Model) 论文名称(Paper) 年份(Year) 被引(cited) 作者(Author) 所属类别(Type) 官方代码(Code) 个人代码(Practice)
Highway Highway Networks 2015 1280(10/09/2020) Rupesh Kumar Srivastava,Klaus Greff,J¨urgen Schmidhuber
PReLU Delving Deep into Rectifiers: Surpassing Human-Level Performance on ImageNet Classification 2015 9108(10/09/2020) Kaiming He,Xiangyu Zhang,Shaoqing Ren,Jian Sun

3. 目标检测(Object Detection)

模型(Model) 论文名称(Paper) 年份(Year) 被引(cited) 作者(Author) 所属类别(Type) 官方代码(Code) 个人代码(Practice)
Selective Search Selective Search for Object Recognition 2013 4498(07/09/2020) J.R.R. Uijlings,et.al
OverFeat OverFeat:Integrated Recognition, Localization and Detection using Convolutional Networks 2014 4061(06/09/2020) Pierre Sermanet,David Eigen,et.al
R-CNN Rich feature hierarchies for accurate object detection and semantic segmentation 2014 14188(06/09/2020) Ross Girshick,Jeff Donahue,et.al
SPPNet Spatial Pyramid Pooling in Deep Convolutional Networks for Visual Recognition 2014 4740(09/09/2020) Kaiming He, Xiangyu Zhang, Shaoqing Ren, Jian Sun
Fast R-CNN Fast R-CNN 2015 10839(08/09/2020) Ross Girshick
Faster R-CNN Faster R-CNN: Towards Real-Time Object Detection with Region Proposal Networks 2016 20864(08/09/2020) Shaoqing Ren, Kaiming He, Ross Girshick, and Jian Sun
YOLO v1 You Only Look Once: Unified, Real-Time Object Detection 2015 10906(11/09/2020) Joseph Redmon, Santosh Divvalay, Ross Girshick, Ali Farhadiy
SSD SSD: Single Shot MultiBox Detector 2015 10131(11/09/2020) Wei Liu, Dragomir Anguelov,et.al

4. 图像分割(Image Segmentation)

模型(Model) 论文名称(Paper) 年份(Year) 被引(cited) 作者(Author) 所属类别(Type) 官方代码(Code) 个人代码(Practice)
FCN Fully Convolutional Networks for Semantic Segmentation 2014 14541(06/09/2020) Jonathan Long*,Evan Shelhamer*,Trevor Darrell
U-Net U-Net: Convolutional Networks for Biomedical Image Segmentation 2015 12052(08/03/2020) Olaf Ronneberger, Philipp Fischer, and Thomas Brox

5. 生成式对抗网络(Generative Adversarial Network, GAN)

模型(Model) 论文名称(Paper) 年份(Year) 被引(cited) 作者(Author) 所属类别(Type) 官方代码(Code) 个人代码(Practice)
GAN Generative Adversarial Networks 2014 30182(05/07/2021) Ian J. Goodfellow, Jean Pouget-Abadie, Mehdi Mirza. et.al

6. 光学字符识别(Optical Character Recognition, OCR)

模型(Model) 论文名称(Paper) 年份(Year) 被引(cited) 作者(Author) 所属类别(Type) 官方代码(Code) 个人代码(Practice)

7. 轻量化网络(Light Networks)

模型(Model) 论文名称(Paper) 年份(Year) 被引(cited) 作者(Author) 所属类别(Type) 官方代码(Code) 个人代码(Practice)
SqueezeNet SqueezeNet: AlexNet-level accuracy with 50x fewer parameters and <0.5MB model size 2016 3862(05/07/2021) Forrest N. Iandola, Song Han. et.al
MobileNet MobileNets: Efficient Convolutional Neural Networks for Mobile Vision Applications 2017 8124(05/07/2021) Andrew G. Howard, Menglong Zhu. et.al
ShuffleNet ShuffleNet: An Extremely Efficient Convolutional Neural Network for Mobile Devices 2017 2430(05/07/2021) Xiangyu Zhang, Xinyu Zhou, Mengxiao Lin, Jian Sun
Xception Xception: Deep Learning with Depthwise Separable Convolutions 2016 5016(05/07/2021) François Chollet

8. 图神经网络(Graph Neural Networks)

模型(Model) 论文名称(Paper) 年份(Year) 被引(cited) 作者(Author) 所属类别(Type) 官方代码(Code) 个人代码(Practice)

9. 人脸识别(Face Recognition)

模型(Model) 论文名称(Paper) 年份(Year) 被引(cited) 作者(Author) 所属类别(Type) 官方代码(Code) 个人代码(Practice)

10. 目标跟踪(Object Tracking)

模型(Model) 论文名称(Paper) 年份(Year) 被引(cited) 作者(Author) 所属类别(Type) 官方代码(Code) 个人代码(Practice)

11. 行人重识别(Person Re-identification, ReID)

模型(Model) 论文名称(Paper) 年份(Year) 被引(cited) 作者(Author) 所属类别(Type) 官方代码(Code) 个人代码(Practice)

12. 雷达点云(Lidar Point Clouds)

模型(Model) 论文名称(Paper) 年份(Year) 被引(cited) 作者(Author) 所属类别(Type) 官方代码(Code) 个人代码(Practice)

13. 3D重建(3D Reconstruction)

模型(Model) 论文名称(Paper) 年份(Year) 被引(cited) 作者(Author) 所属类别(Type) 官方代码(Code) 个人代码(Practice)

14. 图像重建(Image reconstruction)

模型(Model) 论文名称(Paper) 年份(Year) 被引(cited) 作者(Author) 所属类别(Type) 官方代码(Code) 个人代码(Practice)

15. 图像压缩(Image Compression)

模型(Model) 论文名称(Paper) 年份(Year) 被引(cited) 作者(Author) 所属类别(Type) 官方代码(Code) 个人代码(Practice)

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Must-Read CV Papers. 计算机视觉必读论文

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