Yaowei Guo
Papers
1
Total Citations
4
H-Index
1
About
Yaowei Guo is a researcher advancing the frontier of embodied AI and robotic perception, with a core focus on multi-modal 3D human tracking in complex, real-world environments. His most notable contribution is the development of the Siamese Point-Video Transformer, a novel architecture that fuses point cloud and video data to enable robust, jitter-resistant person tracking for robots. Unlike conventional 3D trackers designed for stable driving scenarios, Guo’s work directly addresses the challenges of dynamic, jolting platforms and cluttered surroundings—a critical gap in the field. His 2024 paper on this topic has already garnered early citations, signaling its impact on robotics and human-robot interaction. By tackling the degeneration of traditional trackers in non-ideal conditions, Guo is laying the groundwork for more reliable autonomous systems that can follow and interact with humans in unstructured settings. His research sits at the intersection of computer vision, robotics, and multi-modal learning, offering practical solutions for applications ranging from service robots to search-and-rescue operations.
Research Focus
Key Achievements
Top Papers
- 1