Page 265 - 《软件学报》2025年第5期
P. 265
杨红红 等: 基于平行多尺度时空图卷积网络的三维人体姿态估计算法 2165
[16] Zou ZM, Liu KK, Wang L, Tang W. High-order graph convolutional networks for 3D human pose estimation. In: Proc. of the 31st British
Machine Vision Conf. BMVA Press, 2020.
[17] Li H, Shi BW, Dai WR, Chen YB, Wang BT, Sun Y, Guo M, Li CL, Zou JN, Xiong HK. Hierarchical graph networks for 3D human pose
estimation. In: Proc. of the 32nd British Machine Vision Conf. (BMVC). BMVA Press, 2021. 387.
[18] Chen XP, Lin KY, Liu WT, Qian C, Lin L. Weakly-supervised discovery of geometry-aware representation for 3D human pose
estimation. In: Proc. of the 2019 IEEE/CVF Conf. on Computer Vision and Pattern Recognition (CVPR). Long Beach: IEEE, 2019.
10887–10896. [doi: 10.1109/CVPR.2019.01115]
[19] Chen YL, Wang ZC, Peng YX, Zhang ZQ, Yu G, Sun J. Cascaded pyramid network for multi-person pose estimation. In: Proc. of the
2018 IEEE/CVF Conf. on Computer Vision and Pattern Recognition. Salt Lake City: IEEE, 2018. 7103–7112. [doi: 10.1109/CVPR.2018.
00742]
[20] Chen TL, Fang C, Shen XH, Zhu YH, Chen ZL, Luo JB. Anatomy-aware 3D human pose estimation with bone-based pose
decomposition. IEEE Trans. on Circuits and Systems for Video Technology, 2022, 32(1): 198–209. [doi: 10.1109/TCSVT.2021.3057267]
[21] Lin JH, Lee GH. Trajectory space factorization for deep video-based 3D human pose estimation. In: Proc. of the 30th British Machine
Vision Conf. Cardiff: BMVA Press, 2019. 101.
[22] Li SC, Ke L, Pratama K, Tai YW, Tang CK, Cheng KT. Cascaded deep monocular 3D human pose estimation with evolutionary training
data. In: Proc. of the 2020 IEEE/CVF Conf. on Computer Vision and Pattern Recognition (CVPR). Seattle: IEEE, 2020. 6172–6182. [doi:
10.1109/CVPR42600.2020.00621]
[23] Zheng C, Zhu SJ, Mendieta M, Yang TJN, Chen C, Ding ZM. 3D Human pose estimation with spatial and temporal Transformers. In:
Proc. of the 2021 IEEE/CVF Int’l Conf. on Computer Vision (ICCV). Montreal: IEEE, 2021. 11636–11645. [doi: 10.1109/ICCV48922.
2021.01145]
[24] Xu TH, Takano W. Graph stacked hourglass networks for 3D human pose estimation. In: Proc. of the 2021 IEEE/CVF Conf. on
Computer Vision and Pattern Recognition (CVPR). Nashville: IEEE, 2021. 16100–16109. [doi: 10.1109/CVPR46437.2021.01584]
[25] Martinez J, Hossain R, Romero J, Little JJ. A simple yet effective baseline for 3D human pose estimation. In: Proc. of the 2017 IEEE Int’l
Conf. on Computer Vision (ICCV). Venice: IEEE, 2017. 2659–2668. [doi: 10.1109/ICCV.2017.288]
[26] Liu KK, Ding RQ, Zou ZM, Wang L, Tang W. A comprehensive study of weight sharing in graph networks for 3D human pose
estimation. In: Proc. of the 16th European Conf. on Computer Vision 2020 (ECCV). Glasgow: Springer, 2020. 318–334. [doi: 10.1007/
978-3-030-58607-2_19]
[27] Zeng AL, Sun X, Yang L, Zhao NX, Liu MH, Xu Q. Learning skeletal graph neural networks for hard 3D pose estimation. In: Proc. of the
2021 IEEE/CVF Int’l Conf. on Computer Vision (ICCV). Montreal: IEEE, 2021. 11416–11425. [doi: 10.1109/ICCV48922.2021.01124]
[28] Li WH, Liu H, Tang H, Wang PC, van Gool L. MHFormer: Multi-hypothesis transformer for 3D human pose estimation. In: Proc. of the
2022 IEEE/CVF Conf. on Computer Vision and Pattern Recognition (CVPR). New Orleans: IEEE, 2022. 13137–13146. [doi: 10.1109/
CVPR52688.2022.01280]
[29] Shan WK, Liu ZH, Zhang XF, Wang SS, Ma SW, Gao W. P-STMO: Pre-trained spatial temporal many-to-one model for 3D human pose
estimation. In: Proc. of the 17th European Conf. on Computer Vision (ECCV). Tel Aviv: Springer, 2022. 461–478. [doi: 10.1007/978-3-
031-20065-6_27]
[30] Bai GH, Luo YM, Pan XL, Wang J, Guo JM. Real-time 3D human pose estimation without skeletal a priori structures. Image and Vision
Computing, 2023, 132: 104649. [doi: 10.1016/j.imavis.2023.104649]
[31] Li H, Shi BW, Dai WR, Zheng HW, Wang BT, Sun Y, Guo M, Li CL, Zou JN, Xiong HK. Pose-oriented Transformer with uncertainty-
guided refinement for 2D-to-3D human pose estimation. In: Proc. of the 37th AAAI Conf. on Artificial Intelligence. Washington: AAAI,
2023. 1296–1304. [doi: 10.1609/aaai.v37i1.25213]
[32] Han CC, Yu X, Gao CX, Sang N, Yang Y. Single image based 3D human pose estimation via uncertainty learning. Pattern Recognition,
2022, 132: 108934. [doi: 10.1016/j.patcog.2022.108934]
[33] Wang JB, Yan SJ, Xiong YJ, Lin DH. Motion guided 3D pose estimation from videos. In: Proc. of the 16th European Conf. on Computer
Vision (ECCV). Glasgow: Springer, 2020. 764–780. [doi: 10.1007/978-3-030-58601-0_45]
[34] Yang HH, Liu HX, Zhang YM, Wu XJ. Hierarchical parallel multi-scale graph network for 3D human pose estimation. Applied Soft
Computing, 2023, 140: 110267 [doi: 10.1016/j.asoc.2023.110267]
附中文参考文献:
[1] 张宇, 温光照, 米思娅, 张敏灵, 耿新. 基于深度学习的二维人体姿态估计综述. 软件学报, 2022, 33(11): 4173–4191. http://www.jos.