1 code implementation • 21 Dec 2023 • Xiaolong Shen, Jianxin Ma, Chang Zhou, Zongxin Yang
For 3D GAN inversion, we introduce two methods which aim to enhance the representation of style codes and alleviate 3D inconsistencies.
1 code implementation • CVPR 2023 • Xiaolong Shen, Zongxin Yang, Xiaohan Wang, Jianxin Ma, Chang Zhou, Yi Yang
However, using a single kind of modeling structure is difficult to balance the learning of short-term and long-term temporal correlations, and may bias the network to one of them, leading to undesirable predictions like global location shift, temporal inconsistency, and insufficient local details.
Ranked #46 on 3D Human Pose Estimation on 3DPW
no code implementations • 25 Dec 2022 • Xiaolong Shen, Zhedong Zheng, Yi Yang
As its name suggests, it is made up of two modules: Part-level Spatial Modeling and Part-level Temporal Modeling.
no code implementations • 14 Feb 2019 • Ke Yang, Xiaolong Shen, Peng Qiao, Shijie Li, Dongsheng Li, Yong Dou
The proposed FSN can make dense predictions at frame-level for a video clip using both spatial and temporal context information.