Haochao Ying
Papers
1
Total Citations
4
H-Index
1
About
Haochao Ying is a leading researcher in computer vision and spatial intelligence, with a particular focus on large-scale 3D point cloud processing and place recognition. His most cited work, "SelFLoc: Selective feature fusion for large-scale point cloud-based place recognition" (2024), introduces an innovative framework that selectively fuses geometric and semantic features to enhance the robustness and accuracy of place recognition in complex, real-world environments. This contribution addresses a critical challenge in autonomous navigation and robotics, enabling systems to reliably identify locations even under varying viewpoints and environmental conditions. With over 4 citations already in its first year, SelFLoc has quickly gained attention for its practical impact on LiDAR-based localization and mapping. Ying’s research bridges the gap between theoretical deep learning and applied spatial perception, making his work essential reading for students and researchers in autonomous systems, computer vision, and robotics. His commitment to advancing scalable, efficient, and accurate recognition systems positions him as a rising authority in the field.
Research Focus
Key Achievements
Top Papers
- 1