{"id":17236912,"url":"https://github.com/d-x-y/landmark-detection","last_synced_at":"2025-04-04T06:07:08.286Z","repository":{"id":43808428,"uuid":"124732076","full_name":"D-X-Y/landmark-detection","owner":"D-X-Y","description":"Four landmark detection algorithms, implemented in 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Landmark Detection\n\nThis project contains three landmark detection algorithms, implemented in [PyTorch](pytorch.org).\n\n- Style Aggregated Network for Facial Landmark Detection, CVPR 2018\n- Supervision-by-Registration: An Unsupervised Approach to Improve the Precision of Facial Landmark Detectors, CVPR 2018\n- Teacher Supervises Students How to Learn from Partially Labeled Images for Facial Landmark Detection, ICCV 2019\n- Supervision by Registration and Triangulation for Landmark Detection, TPAMI 2020\n\n\n## Style Aggregated Network for Facial Landmark Detection\n\nThe training and testing codes for [SAN (CVPR 2018)](https://xuanyidong.com/publication/cvpr-2018-san/) are located in the [SAN directory](https://github.com/D-X-Y/landmark-detection/tree/master/SAN).\n\n## Supervision-by-Registration: An Unsupervised Approach to Improve the Precision of Facial Landmark Detectors\n\nThe training and testing codes for [Supervision-by-Registration (CVPR 2018)](https://xuanyidong.com/publication/cvpr-2018-sbr/) are located in the [SBR directory](https://github.com/D-X-Y/landmark-detection/tree/master/SBR).\n\n## Teacher Supervises Students How to Learn from Partially Labeled Images for Facial Landmark Detection\n\nThe model codes for [Teacher Supervises Students (TS3) (ICCV 2019)](https://arxiv.org/abs/1908.02116) are located in the [TS3 directory](https://github.com/D-X-Y/landmark-detection/tree/master/TS3).\n\n## Supervision by Registration and Triangulation for Landmark Detection\n\nThe training and testing codes for [SRT (TPAMI) 2020](https://ieeexplore.ieee.org/document/9050873) are located in the [SRT directory](https://github.com/D-X-Y/landmark-detection/tree/master/SRT).\n\n## Citation\nIf this project helps your research, please cite the following papers:\n```\n@inproceedings{dong2018san,\n   title={Style Aggregated Network for Facial Landmark Detection},\n   author={Dong, Xuanyi and Yan, Yan and Ouyang, Wanli and Yang, Yi},\n   booktitle={Proceedings of the IEEE Conference on Computer Vision and Pattern Recognition (CVPR)},\n   pages={379--388},\n   doi={10.1109/CVPR.2018.00047},\n   year={2018}\n}\n@inproceedings{dong2018sbr,\n  title={{Supervision-by-Registration}: An Unsupervised Approach to Improve the Precision of Facial Landmark Detectors},\n  author={Dong, Xuanyi and Yu, Shoou-I and Weng, Xinshuo and Wei, Shih-En and Yang, Yi and Sheikh, Yaser},\n  booktitle={Proceedings of the IEEE Conference on Computer Vision and Pattern Recognition (CVPR)},\n  pages={360--368},\n  doi={10.1109/CVPR.2018.00045},\n  year={2018}\n}\n@inproceedings{dong2019teacher,\n  title={Teacher Supervises Students How to Learn from Partially Labeled Images for Facial Landmark Detection},\n  author={Dong, Xuanyi and Yang, Yi},\n  booktitle={Proceedings of the IEEE International Conference on Computer Vision (ICCV)},\n  pages={783--792},\n  doi={10.1109/ICCV.2019.00087},\n  year={2019}\n}\n@inproceedings{dong2020srt,\n  title     = {Supervision by Registration and Triangulation for Landmark Detection},\n  author    = {Dong, Xuanyi and Yang, Yi and Wei, Shih-En and Weng, Xinshuo and Sheikh, Yaser and Yu, Shoou-I},\n  journal   = {IEEE Transactions on Pattern Analysis and Machine Intelligence (TPAMI)},\n  volume    = {},\n  number    = {},\n  keywords  = {Landmark Detection;Optical Flow;Triangulation;Deep Learning},\n  doi       = {10.1109/TPAMI.2020.2983935},\n  ISSN      = {1939-3539},\n  year      = {2020},\n  month     = {},\n  note      = {\\mbox{doi}:\\url{10.1109/TPAMI.2020.2983935}}\n}\n```\n\n\n## Contact\nTo ask questions or report issues, please open an issue on the [issues tracker](https://github.com/D-X-Y/landmark-detection/issues).\n","project_url":"https://awesome.ecosyste.ms/api/v1/projects/github.com%2Fd-x-y%2Flandmark-detection","html_url":"https://awesome.ecosyste.ms/projects/github.com%2Fd-x-y%2Flandmark-detection","lists_url":"https://awesome.ecosyste.ms/api/v1/projects/github.com%2Fd-x-y%2Flandmark-detection/lists"}