文献链接

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图像分类(Classification)

• AlexNet http://papers.nips.cc/paper/4824-imagenet-classification-with-deep-convolutional-neural-networks.pdf
• VGG https://arxiv.org/pdf/1409.1556.pdf
• GoogLeNet, Inceptionv1(Going deeper with convolutions) https://arxiv.org/pdf/1409.4842.pdf
• Batch Normalization https://arxiv.org/pdf/1502.03167.pdf
• Inceptionv3(Rethinking the Inception Architecture for Computer Vision) https://arxiv.org/pdf/1512.00567.pdf
• Inceptionv4, Inception-ResNet https://arxiv.org/pdf/1602.07261.pdf
• ResNet https://arxiv.org/pdf/1512.03385.pdf
• ResNeXt https://arxiv.org/pdf/1611.05431.pdf
• DenseNet https://arxiv.org/pdf/1608.06993.pdf
• SENet(Squeeze-and-Excitation Networks) https://arxiv.org/pdf/1709.01507.pdf
• MobileNet(v1) https://arxiv.org/pdf/1704.04861.pdf
• MobileNet(v2) https://arxiv.org/pdf/1801.04381.pdf
• MobileNet(v3) https://arxiv.org/pdf/1905.02244.pdf
• ShuffleNet(v1) https://arxiv.org/pdf/1707.01083.pdf
• ShuffleNet(v2) https://arxiv.org/pdf/1807.11164.pdf
• EfficientNet https://arxiv.org/pdf/1905.11946.pdf
• CSPNet https://arxiv.org/pdf/1911.11929.pdf
• RegNet https://arxiv.org/pdf/2003.13678.pdf

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目标检测(Object Detection)

• R-CNN https://arxiv.org/pdf/1311.2524.pdf
• Fast R-CNN https://arxiv.org/pdf/1504.08083.pdf
• Faster R-CNN https://arxiv.org/pdf/1506.01497.pdf
• Mask R-CNN https://arxiv.org/pdf/1703.06870.pdf
• SSD https://arxiv.org/pdf/1512.02325.pdf
• FPN(Feature Pyramid Networks for Object Detection) https://arxiv.org/pdf/1612.03144.pdf
• RetinaNet(Focal Loss for Dense Object Detection) https://arxiv.org/pdf/1708.02002.pdf
• YOLOv1 https://arxiv.org/pdf/1506.02640.pdf
• YOLOv2 https://arxiv.org/pdf/1612.08242.pdf
• YOLOv3 https://arxiv.org/pdf/1804.02767.pdf
• YOLOv4 https://arxiv.org/pdf/2004.10934.pdf

Others

• Microsoft COCO: Common Objects in Context https://arxiv.org/pdf/1405.0312.pdf
• The PASCALVisual Object Classes Challenge: A Retrospective http://host.robots.ox.ac.uk/pascal/VOC/pubs/everingham15.pdf