oeway / Pytorch Deform Conv
Licence: mit
PyTorch implementation of Deformable Convolution
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PyTorch implementation of Deformable Convolution
- 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):
Also Check out Felix Lau's summary of the paper: https://medium.com/@phelixlau/notes-on-deformable-convolutional-networks-baaabbc11cf3
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