Xuanhua Chen
Papers
1
Total Citations
6
H-Index
1
About
Xuanhua Chen is a rising star in computer vision and graphics, whose research centers on novel view synthesis and 3D scene reconstruction using unconventional visual sensors. His most notable contribution, "IncEventGS: Pose-Free Gaussian Splatting from a Single Event Camera" (2025), pioneers a groundbreaking approach that combines implicit neural representations with explicit 3D Gaussian Splatting (3D-GS) to achieve high-quality novel view synthesis from event cameras—bio-inspired sensors that capture per-pixel brightness changes asynchronously. This work addresses a critical challenge: unlike traditional frame-based cameras (RGB or RGB-D), event cameras lack absolute intensity and pose information, yet Chen’s method enables pose-free, real-time rendering from a single event stream. With 6 citations already in its first year, the paper signals strong early impact in the emerging field of event-based vision. Chen’s research bridges the gap between neuromorphic sensing and modern 3D graphics, offering a path toward robust, low-latency 3D reconstruction in high-speed or low-light scenarios where conventional cameras fail. His work is particularly exciting for students and researchers interested in the intersection of bio-inspired sensors, neural rendering, and efficient 3D representation.
Research Focus
Key Achievements
Top Papers
- 1IncEventGS: Pose-Free Gaussian Splatting from a Single Event Camera6 citations · 2025