PyTorch implementation of Deformable Convolution

Overview

PyTorch implementation of Deformable Convolution

!!!Warning: There is some issues in this implementation and this repo is not maintained any more, please consider using for example: TORCHVISION.OPS.DEFORM_CONV

TODO List

  • implement offsets mapping in pytorch
  • all tests passed
  • deformable convolution module
  • Fine-tuning the deformable convolution modules
  • scaled mnist demo
  • improve speed with cached grid array
  • use MNIST dataset from pytorch (instead of Keras)
  • support input image with different width and height
  • benchmark with tensorflow implementation

Deformable Convolutional Networks

Dai, Jifeng, Haozhi Qi, Yuwen Xiong, Yi Li, Guodong Zhang, Han Hu, and Yichen Wei. 2017. “Deformable Convolutional Networks.” arXiv [cs.CV]. arXiv. http://arxiv.org/abs/1703.06211

The following animation is generated by Felix Lau (with his tensorflow implementation):

Also Check out Felix Lau's summary of the paper: https://medium.com/@phelixlau/notes-on-deformable-convolutional-networks-baaabbc11cf3

Owner
Wei Ouyang
I am working with Deep Learning based image analysis and modeling, excited about biology, deep neural nets, open source, Python and JavaScript.
Wei Ouyang
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