[33] Ze Liu, Yutong Lin, Yue Cao, Han Hu, Yixuan Wei, Zheng Zhang, Stephen Lin, and Baining Guo. Swin transformer: Hierarchical vision transformer using shifted windows. In Proceedings of the IEEE/CVF International Conference on Computer Vision, pages 10012-10022, 2021. 3
[34] Ilya Loshchilov and Frank Hutter. Decoupled weight decay regularization. arXiv preprint arXiv:1711.05101, 2017. 16
[35] Wenjie Luo, Yujia Li, Raquel Urtasun, and Richard Zemel. Understanding the effective receptive field in deep convolutional neural networks. Advances in neural information processing systems, 29, 2016. 5
[36] Xiaoxuan Ma, Jiajun Su, Chunyu Wang, Hai Ci, and Yizhou Wang. Context modeling in 3d human pose estimation: A unified perspective. In Proceedings of the IEEE/CVF conference on computer vision and pattern recognition, pages 6238-6247, 2021. 2
[37] Wei Mao, Richard I Hartley, Mathieu Salzmann, et al. Contact-aware human motion forecasting. Advances in Neural Information Processing Systems, 35:7356-7367, 2022. 1
[38] Julieta Martinez, Rayat Hossain, Javier Romero, and James J Little. A simple yet effective baseline for 3d human pose estimation. In Proceedings of the IEEE international conference on computer vision, pages 2640-2649, 2017. 3
[39] Dushyant Mehta, Helge Rhodin, Dan Casas, Pascal Fua, Oleksandr Sotnychenko, Weipeng Xu, and Christian Theobalt. Monocular 3d human pose estimation in the wild using improved cnn supervision. In 2017 international conference on 3D vision (3DV), pages 506-516. IEEE, 2017. 3, 6, 7, 16
[40] Dushyant Mehta, Srinath Sridhar, Oleksandr Sotnychenko, Helge Rhodin, Mohammad Shafiei, Hans-Peter Seidel, Weipeng Xu, Dan Casas, and Christian Theobalt. Vnect: Real-time 3d human pose estimation with a single rgb camera. Acm transactions on graphics (tog), 36(4):1-14, 2017. 3
[41] Francesc Moreno-Noguer. 3d human pose estimation from a single image via distance matrix regression. In Proceedings of the IEEE conference on computer vision and pattern recognition, pages 2823-2832, 2017. 3
[42] Alejandro Newell, Kaiyu Yang, and Jia Deng. Stacked hourglass networks for human pose estimation. In European conference on computer vision, pages 483-499. Springer, 2016. 3
[43] Georgios Pavlakos, Xiaowei Zhou, and Kostas Daniilidis. Ordinal depth supervision for 3d human pose estimation. In Proceedings of the IEEE conference on computer vision and pattern recognition, pages 7307-7316, 2018. 3
[44] Georgios Pavlakos, Xiaowei Zhou, Konstantinos G Derpanis, and Kostas Daniilidis. Coarse-to-fine volumetric prediction for single-image 3d human pose. In Proceedings of the IEEE conference on computer vision and pattern recognition, pages 7025-7034, 2017. 3
[45] Dario Pavllo, Christoph Feichtenhofer, David Grangier, and Michael Auli. 3d human pose estimation in video with temporal convolutions and semi-supervised training. In CVPR, 2019, 1, 2, 3, 7
[46] Zhongwei Qiu, Qiansheng Yang, Jian Wang, and Dongmei Fu. Iv: An end-to-end instance-guided video transformer for 3d pose estimation. In Proceedings of the 30th ACM International Conference on Multimedia, pages 6174–6182, 2022. 16
[47] Jathushan Rajasegaran, Georgios Pavlakos, Angjoo Kanazawa, and Jitendra Malik. Tracking people by predicting 3d appearance, location and pose. In Proceedings of the IEEE/CVF Conference on Computer Vision and Pattern Recognition, pages 2740-2749, 2022. 1
[48] Olga Russakovsky, Jia Deng, Hao Su, Jonathan Krause, Sanjeev Satheesh, Sean Ma, Zhiheng Huang, Andrej Karpathy, Aditya Khosla, Michael Bernstein, et al. Imagenet large scale visual recognition challenge. International journal of computer vision, 115:211-252, 2015. 9
[49] Shunsuke Saito, Zeng Huang, Ryota Natsume, Shigeo Morishima, Angjoo Kanazawa, and Hao Li. Pifu: Pixel-aligned implicit function for high-resolution clothed human digitization. In Proceedings of the IEEE/CVF international conference on computer vision, pages 2304-2314, 2019. 16
[50] Wenkang Shan, Zhenhua Liu, Xinfeng Zhang, Shanshe Wang, Siwei Ma, and Wen Gao. Pstmo: Pre-trained spatial temporal many-to-one model for 3d human pose estimation. In