no code implementations • 1 Apr 2024 • Zelin He, Ying Sun, Jingyuan Liu, Runze Li
Nonasymptotic bound is provided for the estimation error of the target model, showing the robustness of the proposed method to covariate shifts.
no code implementations • 20 Mar 2024 • Zelin He, Ying Sun, Jingyuan Liu, Runze Li
We consider the transfer learning problem in the high dimensional setting, where the feature dimension is larger than the sample size.
no code implementations • 22 Jan 2024 • Zhenzhen Weng, Jingyuan Liu, Hao Tan, Zhan Xu, Yang Zhou, Serena Yeung-Levy, Jimei Yang
We present Human-LRM, a diffusion-guided feed-forward model that predicts the implicit field of a human from a single image.
no code implementations • CVPR 2022 • Jingbo Wang, Yu Rong, Jingyuan Liu, Sijie Yan, Dahua Lin, Bo Dai
The ability to synthesize long-term human motion sequences in real-world scenes can facilitate numerous applications.
no code implementations • ICCV 2021 • Jingyuan Liu, Mingyi Shi, Qifeng Chen, Hongbo Fu, Chiew-Lan Tai
We present a novel approach for extracting human pose features from human action videos.
no code implementations • 19 Aug 2019 • Wanjun Liu, Yuan Ke, Jingyuan Liu, Runze Li
It can be shown that the proposed two-step approach enjoys both sure screening and FDR control if the pre-specified FDR level $\alpha$ is greater or equal to $1/s$, where $s$ is the number of active features.