TorchVision models

Source: Pytorch/Vision repo

(inceptionv3 included in Inception*)

ResNet*

K. He, X. Zhang, S. Ren, and J. Sun, “Deep residual learning for image recognition,” in Conference on Computer Vision and Pattern Recognition (CVPR). IEEE, 2016, pp. 770–778.

@inproceedings{he2016deep,
  title={Deep residual learning for image recognition},
  author={He, Kaiming and Zhang, Xiangyu and Ren, Shaoqing and Sun, Jian},
  booktitle={Conference on Computer Vision and Pattern Recognition (CVPR)},
  pages={770--778},
  year={2016},
  organization={IEEE}

• resnet18(num_classes=1000, pretrained='imagenet')
• resnet34(num_classes=1000, pretrained='imagenet')
• resnet50(num_classes=1000, pretrained='imagenet')
• resnet101(num_classes=1000, pretrained='imagenet')
• resnet152(num_classes=1000, pretrained='imagenet')

DenseNet*

G. Huang, Z. Liu, K. Q. Weinberger, and L. van der Maaten, “Densely connected convolutional networks,” in Conference on Computer Vision and Pattern Recognition (CVPR), vol. 1, no. 2. IEEE, 2017, p. 3.

@inproceedings{huang2017densely,
  title={Densely connected convolutional networks},
  author={Huang, Gao and Liu, Zhuang and Weinberger, Kilian Q and van der Maaten, Laurens},
  booktitle={Conference on Computer Vision and Pattern Recognition (CVPR)},
  volume={1},
  number={2},
  pages={3},
  year={2017},
  organization={IEEE}
}

• densenet121(num_classes=1000, pretrained='imagenet')
• densenet161(num_classes=1000, pretrained='imagenet')
• densenet169(num_classes=1000, pretrained='imagenet')
• densenet201(num_classes=1000, pretrained='imagenet')

SqueezeNet*

• squeezenet1_0(num_classes=1000, pretrained='imagenet')
• squeezenet1_1(num_classes=1000, pretrained='imagenet')
• alexnet(num_classes=1000, pretrained='imagenet')
• vgg11(num_classes=1000, pretrained='imagenet')
• vgg13(num_classes=1000, pretrained='imagenet')
• vgg16(num_classes=1000, pretrained='imagenet')
• vgg19(num_classes=1000, pretrained='imagenet')
• vgg11_bn(num_classes=1000, pretrained='imagenet')
• vgg13_bn(num_classes=1000, pretrained='imagenet')
• vgg16_bn(num_classes=1000, pretrained='imagenet')
• vgg19_bn(num_classes=1000, pretrained='imagenet')