no code implementations • ICCV 2017 • Zefan Li, Bingbing Ni, Wenjun Zhang, Xiaokang Yang, Wen Gao
Input binarization has shown to be an effective way for network acceleration.
no code implementations • CVPR 2018 • Jingwei Xu, Bingbing Ni, Zefan Li, Shuo Cheng, Xiaokang Yang
Despite recent emergence of adversarial based methods for video prediction, existing algorithms often produce unsatisfied results in image regions with rich structural information (i. e., object boundary) and detailed motion (i. e., articulated body movement).
no code implementations • ECCV 2018 • Yang Shen, Bingbing Ni, Zefan Li, Ning Zhuang
Predicting future activities from an egocentric viewpoint is of particular interest in assisted living.
no code implementations • CVPR 2021 • Zefan Li, Chenxi Liu, Alan Yuille, Bingbing Ni, Wenjun Zhang, Wen Gao
For a given unsupervised task, we design multilevel tasks and define different learning stages for the deep network.
no code implementations • 16 Mar 2022 • Zefan Li, Bingbing Ni, Teng Li, Wenjun Zhang, Wen Gao
GCGD consists of two plug-in modules: 1) inspired by the idea of gradient prediction, we propose a \textbf{GC-W} module for weight gradient correction; 2) based on Neural ODE, we propose a \textbf{GC-ODE} module for hidden states gradient correction.