Test-time Personalizable Forecasting of 3D Human Poses
Embedded Files
Paper accepted by ICCV 2023
Qiongjie Cui, Huaijiang Sun, Jianfeng Lu, Weiqing Li, Bin Li, Hongwei Yi, Haofan Wang
We propose a new task: How to perform high-fidelity predictions when there are distribution gaps between testing and training characters ?
Demo Video and Visulazition of Our Method
(Eating activity) Predicted poses of SOTA method (ECCV23) and ours+SPGSN
SPGSN (ECCV23)
MPJPE (at end pose)=73.4mm
SPGSN w/ H/PTTP
MPJPE (at end pose)=67.3mm:
(Smoking activity) Predicted poses of SOTA method (ECCV23) and ours+SPGSN
SPGSN (ECCV23)
MPJPE (at end pose)=68.6mm
SPGSN w/ H/PTTP
MPJPE (at end pose)=63.7mm
(Discussion activity) Predicted poses of SOTA method (ECCV23) and ours+SPGSN
SPGSN (ECCV23)
MPJPE (at end pose)=116.8mm
SPGSN w/ H/PTTP
MPJPE (at end pose)=112.5mm
Cite this paper using the following context:
@inproceedings{cui2023test,
title={Test-time Personalizable Forecasting of 3D Human Poses},
author={Qiongjie Cui, Huaijiang Sun, Jianfeng Lu, Weiqing Li, Bin Li, Hongwei Yi, Haofan Wang},
booktitle={ICCV},
year={2023}
}
The camera-ready paper is available at: https://drive.google.com/file/d/1LWtw-JmSqRodN1fNSgGL6wUdOEKw5uWu/view?usp=drive_link
Code will be publicly released.
This work is partly supported by Xiaohongshu Inc. China
Page updated
Google Sites
Report abuse