Zhenxiang Lin
Papers
2
Total Citations
7
H-Index
2
About
Zhenxiang Lin is a pioneering researcher in 3D computer vision and multi-modal perception, with a focus on bridging natural language and real-world dynamic environments. His most significant contribution is the development of **WildRefer**, a groundbreaking framework for 3D object localization in large-scale dynamic scenes using multi-modal visual data—integrating 2D images, 3D LiDAR point clouds, and natural language descriptions. This work addresses the challenging task of 3D visual grounding in unstructured, outdoor settings, enabling machines to understand and locate objects based on human linguistic cues in real-time. With over 7 citations across two versions of the paper (2023–2024), WildRefer has quickly gained attention for its novel approach to fusing rich appearance and geometric information. Lin’s research pushes the boundaries of autonomous navigation, augmented reality, and human-robot interaction, where robust perception in changing environments is critical. His work stands out for tackling the gap between controlled indoor benchmarks and the complexity of the wild, making him a rising voice in multi-modal AI and embodied intelligence.
Research Focus
Key Achievements
Top Papers
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- 2