@@ -11,10 +12,23 @@ created by [Hang Zhang](http://hangzh.com/)
- Please visit the [**Docs**](http://hangzh.com/PyTorch-Encoding/) for detail instructions of installation and usage.
- Please visit the [link](http://hangzh.com/PyTorch-Encoding/experiments/segmentation.html) to examples of semantic segmentation.
- Please visit the [link](http://hangzh.com/PyTorch-Encoding/model_zoo/imagenet.html) to image classification models.
- Please visit the [link](http://hangzh.com/PyTorch-Encoding/model_zoo/segmentation.html) to semantic segmentation models.
## Citations
**ResNeSt: Split-Attention Networks**[[arXiv]]()
[Hang Zhang](http://hangzh.com/), Chongruo Wu, Zhongyue Zhang, Yi Zhu, Zhi Zhang, Haibin Lin, Yue Sun, Tong He, Jonas Muller, R. Manmatha, Mu Li and Alex Smola
```
@article{zhang2020resnest,
title={ResNeSt: Split-Attention Networks},
author={Zhang, Hang and Wu, Chongruo and Zhang, Zhongyue and Zhu, Yi and Zhang, Zhi and Lin, Haibin and Sun, Yue and He, Tong and Muller, Jonas and Manmatha, R. and Li, Mu and Smola, Alexander},
journal={arXiv preprint},
year={2020}
}
```
**Context Encoding for Semantic Segmentation**[[arXiv]](https://arxiv.org/pdf/1803.08904.pdf)
- Current PyTorch DataParallel Table is not supporting mutl-gpu loss calculation, which makes the gpu memory usage very in-balance. We address this issue here by doing DataParallel for Model & Criterion.
.. note::
This code is provided together with the paper
* Hang Zhang, Kristin Dana, Jianping Shi, Zhongyue Zhang, Xiaogang Wang, Ambrish Tyagi, Amit Agrawal. "Context Encoding for Semantic Segmentation" *The IEEE Conference on Computer Vision and Pattern Recognition (CVPR) 2018*
Deprecated, please use torch.nn.parallel.DistributedDataParallel with :class:`encoding.nn.DistSyncBatchNorm` for the best performance.
