Basic Information
I am a PhD student in the Computer Vision and Learning Group (VLG) at ETH Zürich, under the supervision of Prof. Siyu Tang. Additionally, I have had the pleasure of collaborating with Thabo Beeler. I obtained my Master's degree in Computer Science with distinction from ETH Zürich in 2022, and my Bachelor's degree in Computer Science from Beihang University in 2019.
My research focuses on the intersection of computer vision and computer graphics, particularly in human motion modeling and the synthesis of human-scene interaction behaviors. My doctoral research is supported by the Swiss Data Science Center (SDSC) PhD fellowship.
Social
Publications
Authors:Kaifeng Zhao, Gen Li, Siyu Tang
DART is a Diffusion-based Autoregressive motion model for Real-time Text-driven motion control. Furthermore, DART enables various motion generation applications with spatial constraints and goals, including motion in-between, waypoint goal reaching, and human-scene interaction generation.
EgoGen: An Egocentric Synthetic Data Generator
Conference: Conference on Computer Vision and Pattern Recognition (CVPR 2024) oral presentation
Authors:Gen Li, Kaifeng Zhao, Siwei Zhang, Xiaozhong Lyu, Mihai Dusmanu, Yan Zhang, Marc Pollefeys, Siyu Tang
EgoGen is new synthetic data generator that can produce accurate and rich ground-truth training data for egocentric perception tasks.
Authors:Kaifeng Zhao, Yan Zhang, Shaofei Wang, Thabo Beeler, Siyu Tang
Interaction with environments is one core ability of virtual humans and remains a challenging problem. We propose a method capable of generating a sequence of natural interaction events in real cluttered scenes.
Authors:Kaifeng Zhao, Shaofei Wang, Yan Zhang, Thabo Beeler, Siyu Tang
Synthesizing natural interactions between virtual humans and their 3D environments is critical for numerous applications, such as computer games and AR/VR experiences. We propose COINS, for COmpositional INteraction Synthesis with Semantic Control.