no code implementations • CVPR 2023 • Sijing Wu, Yichao Yan, Yunhao Li, Yuhao Cheng, Wenhan Zhu, Ke Gao, Xiaobo Li, Guangtao Zhai
To bring digital avatars into people's lives, it is highly demanded to efficiently generate complete, realistic, and animatable head avatars.
no code implementations • 24 Aug 2022 • Yuanliang Zhang, XiaoFeng Wang, Jinxin Hu, Ke Gao, Chenyi Lei, Fei Fang
we summarize three practical challenges which are not well solved for multi-scenario modeling: (1) Lacking of fine-grained and decoupled information transfer controls among multiple scenarios.
no code implementations • 18 Jun 2021 • Baoming Yan, Lin Wang, Ke Gao, Bo Gao, Xiao Liu, Chao Ban, Jiang Yang, Xiaobo Li
Video affective understanding, which aims to predict the evoked expressions by the video content, is desired for video creation and recommendation.
1 code implementation • CVPR 2021 • Lei LI, Ke Gao, Juan Cao, Ziyao Huang, Yepeng Weng, Xiaoyue Mi, Zhengze Yu, Xiaoya Li, Boyang xia
A series of strategies are introduced to guarantee the safety and effectiveness of the expanded domains.
no code implementations • 1 Jan 2019 • Jiarong Dong, Ke Gao, Xiaokai Chen, Junbo Guo, Juan Cao, Yongdong Zhang
To address this issue, we propose a novel learning strategy called Information Loss, which focuses on the relationship between the video-specific visual content and corresponding representative words.
no code implementations • 19 May 2018 • Xiaokai Chen, Ke Gao
1) A novel compact representation of video which distills its significant spatial-temporal evolution into a matrix called DenseImage, primed for efficient video encoding.
3 code implementations • 18 Jul 2017 • Shiwei Shen, Guoqing Jin, Ke Gao, Yongdong Zhang
Although neural networks could achieve state-of-the-art performance while recongnizing images, they often suffer a tremendous defeat from adversarial examples--inputs generated by utilizing imperceptible but intentional perturbation to clean samples from the datasets.
no code implementations • CVPR 2017 • Xishan Zhang, Ke Gao, Yongdong Zhang, Dongming Zhang, Jintao Li, Qi Tian
This paper contributes to: 1)The first in-depth study of the weakness inherent in data-driven static fusion methods for video captioning.