Very Deep Convolutional Networks for Large-Scale Image Recognition

Last update: Dec 05, 2022

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Deep Learning pytorch-vgg

Overview

pytorch-vgg

Some scripts to convert the VGG-16 and VGG-19 models [1] from Caffe to PyTorch.

The converted models can be used with the PyTorch model zoo and are available here:

VGG-16: https://web.eecs.umich.edu/~justincj/models/vgg16-00b39a1b.pth

VGG-19: https://web.eecs.umich.edu/~justincj/models/vgg19-d01eb7cb.pth

These models expect different preprocessing than the other models in the PyTorch model zoo. Images should be in BGR format in the range [0, 255], and the following BGR values should then be subtracted from each pixel: [103.939, 116.779, 123.68]

[1] Karen Simonyan and Andrew Zisserman, "Very Deep Convolutional Networks for Large-Scale Image Recognition", ICLR 2015

Owner

Justin Johnson

GitHub Repository

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Very Deep Convolutional Networks for Large-Scale Image Recognition

Related tags

Overview

pytorch-vgg

Owner

Justin Johnson

Code and models for "Pano3D: A Holistic Benchmark and a Solid Baseline for 360 Depth Estimation", OmniCV Workshop @ CVPR21.

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