Xiaoxiao Geng

Papers

Total Citations

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About

Xiaoxiao Geng is a leading researcher in 3D computer vision and autonomous perception, with a primary focus on LiDAR point cloud analysis. Her most impactful work introduces the Multi-Scale Attentive Aggregation Network (MSAAN), a novel architecture that achieves global consistency in point cloud feature representation for semantic segmentation. This breakthrough, published in 2021 and garnering 32 citations, directly addresses critical challenges in self-driving vehicles, robotics, and augmented reality by enabling machines to parse complex 3D environments with unprecedented accuracy. Geng’s approach leverages multi-scale attentive aggregation to capture both fine-grained local details and broad contextual patterns, setting a new standard for segmentation performance. Her contributions are foundational for advancing real-world autonomous systems, where reliable scene understanding is paramount. Through this work, Geng has established herself as a key innovator in point cloud processing, bridging the gap between theoretical deep learning and practical deployment in safety-critical applications. Her research continues to inspire new directions in efficient, high-fidelity 3D perception.