Yancheng Pan

Papers

Total Citations

110

H-Index

About

Yancheng Pan is a leading researcher in 3D computer vision, with a primary focus on LiDAR-based semantic segmentation for autonomous driving and robotics. His work addresses a critical bottleneck in the field: the extreme labor and expertise required to produce fine-annotated 3D LiDAR datasets. Pan’s most influential contribution, the 2021 survey “Are We Hungry for 3D LiDAR Data for Semantic Segmentation? A Survey of Datasets and Methods,” has garnered 99 citations, establishing itself as a key reference for researchers navigating the landscape of deep learning techniques and dataset limitations in this domain. By systematically reviewing state-of-the-art methods and exposing performance constraints, Pan has helped the community understand where algorithmic and data-driven progress is most needed. His earlier works from 2020 further laid the groundwork for this comprehensive analysis, collectively shaping how researchers approach 3D semantic segmentation. Through his surveys and experimental studies, Pan has provided a vital roadmap for developing more efficient, data-aware models—directly impacting the advancement of safer, more capable autonomous systems.