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https://github.com/oeway/pytorch-deform-conv

PyTorch implementation of Deformable Convolution
https://github.com/oeway/pytorch-deform-conv

deep-learning deep-learning-algorithms

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PyTorch implementation of Deformable Convolution

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# 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](https://pytorch.org/vision/stable/_modules/torchvision/ops/deform_conv.html)**

* By Wei OUYANG @ Institut Pasteur
* Thanks to Felix Lau's Keras/TensorFlow implementation: ~~https://github.com/felixlaumon/deform-conv~~ (https://github.com/kastnerkyle/deform-conv)

### TODO List
- [x] implement offsets mapping in pytorch
- [x] all tests passed
- [x] deformable convolution module
- [x] Fine-tuning the deformable convolution modules
- [x] scaled mnist demo
- [x] 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):

![](deformable-learned-offset-filtered.gif)

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