Symbiotic Graph Neural Networks for 3D Skeleton-based Human Action Recognition and Motion Prediction
Comments submitted to IEEE-TPAMI
期刊&会议
IEEE Transactions on Pattern Analysis and Machine Intelligence · 期刊 · Computer Vision
Comments submitted to IEEE-TPAMI
Journal ref IEEE TRANSACTIONS ON PATTERN ANALYSIS AND MACHINE INTELLIGENCE 2019
Comments IEEE Transactions on Pattern Analysis and Machine Intelligence (2019). Together with Supplementary Materials. Note: The author list in Google Scholar is INCORRECT. The right author list is 1) Yan Li, 2) Junge Zhang, 3) Kaiqi Huang and 4) Jianguo Zhang. The official published version can be found in https://ieeexplore.ieee.org/abstract/document/8304628
Comments Accepted to TPAMI (SI RGB-D Vision), code https://github.com/andrea-pilzer/PFN-depth
Comments 16 pages, accepted by IEEE T-PAMI
Journal ref IEEE Transactions on Pattern Analysis and Machine Intelligence,2019
Comments 14 pages, 7 pages. Accepted to TPAMI
Journal ref IEEE Transactions on Pattern Analysis and Machine Intelligence,2019
Comments To appear in IEEE Transactions on Pattern Analysis and Machine Intelligence
Comments Accepted in Transactions on Pattern Analysis and Machine Intelligence (TPAMI)
Comments Accepted by TPAMI. arXiv admin note: substantial text overlap with arXiv:1712.07195
Comments Accepted by TPAMI. An extension of the conference version. arXiv admin note: text overlap with arXiv:1807.02242
Comments IEEE Transactions on Pattern Analysis and Machine Intelligence (TPAMI) 2019. arXiv admin note: substantial text overlap with arXiv:1804.02142
Comments 24 Pages, 12 Figures, 6 Tables and 3 Algorithms
Journal ref IEEE Transactions on Pattern Analysis and Machine Intelligence, 40(7), 2017
Comments Journal preprint of arXiv:1607.02586 (IEEE TPAMI, 2019). The first two authors contributed equally to this work. Project page: http://visualdynamics.csail.mit.edu
Journal ref IEEE Transactions on Pattern Analysis and Machine Intelligence (TPAMI), vol. 41, no. 9, pp. 2236-2250, 2019
Comments 14 pages, 5 figures
Journal ref IEEE Transactions on Pattern Analysis and Machine Intelligence 2019
Comments 14 pages, 14 Figures
Journal ref IEEE Transactions on Pattern Analysis and Machine Intelligence 2019
Comments 15 pages; 17 figures
Journal ref IEEE Transactions on Pattern Analysis and Machine Intelligence, 2019
Comments To appear in IEEE Transactions on Pattern Analysis and Machine Intelligence. Matlab code is available from Google drive at https://drive.google.com/open?id=1SlxzEOX8RbnLwCgRyqGwMOL7vuT90Gje or Baidu Cloud at https://pan.baidu.com/s/1xupfXCmIV20gXPr0TicGkg (access code: d1sa)
Comments Accepted to IEEE Transactions on Pattern Analysis and Machine Intelligence
Comments IEEE Transactions on Pattern Analysis and Machine Intelligence, 18 pages, 15 figures, 11 tables. arXiv admin note: substantial text overlap with arXiv:1806.10779
Comments Accepted by TPAMI. Examples and code: https://cvjena.github.io/libmaxdiv/
Journal ref IEEE Transactions on Pattern Analysis and Machine Intelligence, vol. 41, no. 5, pp. 1088-1101, 1 May 2019
Journal ref IEEE Transactions on Pattern Analysis and Machine Intelligence ( Volume: 40 , Issue: 2 , Feb. 1 2018 )
Journal ref IEEE TRANSACTIONS ON PATTERN ANALYSIS AND MACHINE INTELLIGENCE, VOL. 34, NO. 3, MARCH 2012
Comments To appear in IEEE TPAMI
Comments IEEE Transactions on Pattern Analysis and Machine Intelligence (TPAMI). Conference version: arXiv:1804.03786 (CVPR'18). Source code: https://github.com/tranluan/Nonlinear_Face_3DMM , Project webpage: http://cvlab.cse.msu.edu/project-nonlinear-3dmm.html
Comments Published in TPAMI 2019. arXiv admin note: substantial text overlap with arXiv:1807.08186
Comments Chenxu Luo, Zhenheng Yang, and Peng Wang contributed equally, TPAMI submission
Comments IEEE Transactions on Pattern Analysis and Machine Intelligence
Comments Accepted as regular paper in IEEE Transactions on Pattern Analysis and Machine Intelligence (TPAMI). Substantial text overlap with arXiv:1712.01892
Comments Version 4: Accepted by TPAMI. Version 3: 17 pages, 10 tables, 11 figures, added the application (DeLS-3D) based on the ApolloScape Dataset. Version 2: 7 pages, 6 figures, added comparison with BDD100K dataset