1 code implementation • 18 Jan 2024 • Xuangeng Chu, Yu Li, Ailing Zeng, Tianyu Yang, Lijian Lin, Yunfei Liu, Tatsuya Harada
Head avatar reconstruction, crucial for applications in virtual reality, online meetings, gaming, and film industries, has garnered substantial attention within the computer vision community.
no code implementations • ICCV 2023 • Yunfei Liu, Lijian Lin, Fei Yu, Changyin Zhou, Yu Li
Audio-driven portrait animation aims to synthesize portrait videos that are conditioned by given audio.
no code implementations • 30 Jan 2023 • Yizhen Chen, Jie Wang, Lijian Lin, Zhongang Qi, Jin Ma, Ying Shan
Vision-language alignment learning for video-text retrieval arouses a lot of attention in recent years.
no code implementations • ICCV 2023 • Tianke Zhang, Xuangeng Chu, Yunfei Liu, Lijian Lin, Zhendong Yang, Zhengzhuo Xu, Chengkun Cao, Fei Yu, Changyin Zhou, Chun Yuan, Yu Li
However, the current deep learning-based methods face significant challenges in achieving accurate reconstruction with disentangled facial parameters and ensuring temporal stability in single-frame methods for 3D face tracking on video data.
no code implementations • 10 May 2022 • Lijian Lin, Xintao Wang, Zhongang Qi, Ying Shan
In this work, we show that it is possible to gradually train video models from small to large spatial/temporal sizes, i. e., in an easy-to-hard manner.
no code implementations • 9 Nov 2020 • Lijian Lin, Haosheng Chen, Yanjie Liang, Yan Yan, Hanzi Wang
In this paper, we propose a robust tracking method via Statistical Positive sample generation and Gradient Aware learning (SPGA) to address the above two limitations.
no code implementations • 16 Sep 2020 • Lijian Lin, Haosheng Chen, Honglun Zhang, Jun Liang, Yu Li, Ying Shan, Hanzi Wang
Video object detection is a tough task due to the deteriorated quality of video sequences captured under complex environments.