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[Enhancement] Change readme style and Update metafiles. (#895) 
* [Enhancement] Change readme style and prepare for metafiles update.

* Update apcnet github repo url.

* add code snippet.

* split code snippet & official repo.

* update md2yml hook.

* Update metafiles.

* Add converted from attribute.

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* update bisenet v2 metafile.

* checkout to ubuntu environment.

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Co-authored-by: Junjun2016 <hejunjun@sjtu.edu.cn>
 		2021-09-28 16:25:37 +08:00
..
README.md [Enhancement] Change readme style and Update metafiles. (#895) 2021-09-28 16:25:37 +08:00
bisenetv2.yml [Enhancement] Change readme style and Update metafiles. (#895) 2021-09-28 16:25:37 +08:00
bisenetv2_fcn_4x4_1024x1024_160k_cityscapes.py [Feature] Support BiSeNetV2 (#804) 2021-09-26 18:52:16 +08:00
bisenetv2_fcn_4x8_1024x1024_160k_cityscapes.py [Feature] Support BiSeNetV2 (#804) 2021-09-26 18:52:16 +08:00
bisenetv2_fcn_fp16_4x4_1024x1024_160k_cityscapes.py [Feature] Support BiSeNetV2 (#804) 2021-09-26 18:52:16 +08:00
bisenetv2_fcn_ohem_4x4_1024x1024_160k_cityscapes.py [Feature] Support BiSeNetV2 (#804) 2021-09-26 18:52:16 +08:00

README.md

Bisenet v2: Bilateral Network with Guided Aggregation for Real-time Semantic Segmentation

Introduction

Official Repo

Code Snippet

BiSeNetV2 (IJCV'2021) 
@article{yu2021bisenet,
  title={Bisenet v2: Bilateral network with guided aggregation for real-time semantic segmentation},
  author={Yu, Changqian and Gao, Changxin and Wang, Jingbo and Yu, Gang and Shen, Chunhua and Sang, Nong},
  journal={International Journal of Computer Vision},
  pages={1--18},
  year={2021},
  publisher={Springer}
}

Results and models

Cityscapes

Method Backbone Crop Size Lr schd Mem (GB) Inf time (fps) mIoU mIoU(ms+flip) config download
BiSeNetV2 BiSeNetV2 1024x1024 160000 7.64 31.77 73.21 75.74 config model | log
BiSeNetV2 (OHEM) BiSeNetV2 1024x1024 160000 7.64 - 73.57 75.80 config model | log
BiSeNetV2 (4x8) BiSeNetV2 1024x1024 160000 15.05 - 75.76 77.79 config model | log
BiSeNetV2 (FP16) BiSeNetV2 1024x1024 160000 5.77 36.65 73.07 75.13 config model | log

Note:

  • OHEM means Online Hard Example Mining (OHEM) is adopted in training.
  • FP16 means Mixed Precision (FP16) is adopted in training.
  • 4x8 means 4 GPUs with 8 samples per GPU in training.