@misc{https://doi.org/10.48550/arxiv.2107.03332,
title={SimCC: a Simple Coordinate Classification Perspective for Human Pose Estimation},
author={Li, Yanjie and Yang, Sen and Liu, Peidong and Zhang, Shoukui and Wang, Yunxiao and Wang, Zhicheng and Yang, Wankou and Xia, Shu-Tao},
year={2021}
}
@inproceedings{sandler2018mobilenetv2,
title={Mobilenetv2: Inverted residuals and linear bottlenecks},
author={Sandler, Mark and Howard, Andrew and Zhu, Menglong and Zhmoginov, Andrey and Chen, Liang-Chieh},
booktitle={Proceedings of the IEEE conference on computer vision and pattern recognition},
pages={4510--4520},
year={2018}
}
@inproceedings{lin2014microsoft,
title={Microsoft coco: Common objects in context},
author={Lin, Tsung-Yi and Maire, Michael and Belongie, Serge and Hays, James and Perona, Pietro and Ramanan, Deva and Doll{\'a}r, Piotr and Zitnick, C Lawrence},
booktitle={European conference on computer vision},
pages={740--755},
year={2014},
organization={Springer}
}
Results on COCO val2017 with detector having human AP of 56.4 on COCO val2017 dataset
Arch | Input Size | AP | AP50 | AP75 | AR | AR50 | ckpt | log |
---|---|---|---|---|---|---|---|---|
simcc_mobilenetv2_wo_deconv | 256x192 | 0.620 | 0.855 | 0.697 | 0.678 | 0.902 | ckpt | log |