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2019-11-10 00:15:31 +11:00
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README.md
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@@ -5,7 +5,6 @@ This project contains the following neural architecture search algorithms, imple
- Network Pruning via Transformable Architecture Search, NeurIPS 2019
- One-Shot Neural Architecture Search via Self-Evaluated Template Network, ICCV 2019
- Searching for A Robust Neural Architecture in Four GPU Hours, CVPR 2019
- Auto-ReID: Searching for a Part-Aware ConvNet for Person Re-Identification, ICCV 2019
- several typical classification models, e.g., ResNet and DenseNet (see BASELINE.md)
@@ -104,12 +103,6 @@ CUDA_VISIBLE_DEVICES=0 bash ./scripts-search/algos/DARTS-V2.sh cifar10 -1
```
## [Auto-ReID: Searching for a Part-Aware ConvNet for Person Re-Identification](https://arxiv.org/abs/1903.09776)
The part-aware module is defined at [here](https://github.com/D-X-Y/NAS-Projects/blob/master/lib/models/cell_searchs/operations.py#L85).
For more questions, please contact Ruijie Quan (Ruijie.Quan@student.uts.edu.au).
# Citation
If you find that this project helps your research, please consider citing some of the following papers: