Papers
2
Total Citations
7
H-Index
2
About
Yuenan Hou is a researcher advancing the frontier of 3D scene understanding through multi-modal perception and natural language interaction. His primary research areas include 3D object localization, visual grounding, and the integration of LiDAR point clouds with 2D imagery for dynamic, real-world environments. Hou’s most notable contribution is the development of **WildRefer**, a pioneering framework that tackles the challenging task of 3D visual grounding in large-scale, dynamic scenes. By fusing natural language descriptions with online-captured multi-modal visual data—combining 2D images and 3D LiDAR point clouds—WildRefer enables precise object localization in complex, ever-changing settings. This work, published in 2023 and 2024, has garnered early recognition with 7 citations, signaling its growing influence in the computer vision and robotics communities. Hou’s approach stands out for its practical applicability to autonomous driving and augmented reality, where understanding a scene through both visual and linguistic cues is critical. His research bridges the gap between human language and machine perception, offering a robust solution for navigating and interacting with unstructured environments.
Research Focus
Key Achievements
Top Papers
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- 2