no code implementations • 26 Mar 2024 • He Zhang, Shenghao Ren, Haolei Yuan, Jianhui Zhao, Fan Li, Shuangpeng Sun, Zhenghao Liang, Tao Yu, Qiu Shen, Xun Cao
To validate the dataset, we propose an RGBD-P SMPL fitting method and also a monocular-video-based baseline framework, VP-MoCap, for human motion capture.
no code implementations • CVPR 2023 • Zhijun Zhai, Jianhui Zhao, Chengjiang Long, Wenju Xu, Shuangjiang He, Huijuan Zhao
Micro-expressions are spontaneous, rapid and subtle facial movements that can neither be forged nor suppressed.
Micro Expression Recognition Micro-Expression Recognition +2
1 code implementation • 16 Sep 2021 • Xue Jiang, Jianhui Zhao, Bo Du, Zhiyong Yuan
In detail, the network's performance depends on the choice of transformations and the amount of unlabeled data used in the training process of self-supervised learning.
no code implementations • 28 Oct 2020 • QiFeng Lin, Jianhui Zhao, Gang Fu, and Zhiyong Yuan, Member, IEEE
Extensive experiments on the public Dataset for Object deTection in Aerial images data set indicate that our CRPN can help our detector deal the larger image faster with the limited GPU memory; meanwhile, the SFNet is beneficial to achieve more accurate detection of geospatial objects with wide-scale range.
no code implementations • CVPR 2019 • Tao Yu, Zerong Zheng, Yuan Zhong, Jianhui Zhao, Qionghai Dai, Gerard Pons-Moll, Yebin Liu
This paper proposes a new method for live free-viewpoint human performance capture with dynamic details (e. g., cloth wrinkles) using a single RGBD camera.
no code implementations • CVPR 2018 • Tao Yu, Zerong Zheng, Kaiwen Guo, Jianhui Zhao, Qionghai Dai, Hao Li, Gerard Pons-Moll, Yebin Liu
We further propose a joint motion tracking method based on the double layer representation to enable robust and fast motion tracking performance.
no code implementations • ICCV 2017 • Tao Yu, Kaiwen Guo, Feng Xu, Yuan Dong, Zhaoqi Su, Jianhui Zhao, Jianguo Li, Qionghai Dai, Yebin Liu
To reduce the ambiguities of the non-rigid deformation parameterization on the surface graph nodes, we take advantage of the internal articulated motion prior for human performance and contribute a skeleton-embedded surface fusion (SSF) method.