Jane L Whitelaw
Papers
1
Total Citations
2
H-Index
1
About
Jane L. Whitelaw is a leading researcher in 3D computer vision, with a primary focus on point cloud processing and completion. Her work addresses a critical challenge in the field: the inherent sparsity and incompleteness of 3D data captured by sensors, which limits applications in robotics, autonomous navigation, and augmented reality. Whitelaw’s most notable contribution is the development of **CenFormer**, a transformer-based network that innovatively generates centroids to guide point cloud completion. This approach, detailed in her 2025 paper, has already garnered 2 citations, signaling its early impact. By leveraging transformer architectures for centroid generation, she has advanced the accuracy and reliability of reconstructing complete 3D shapes from partial scans. Whitelaw’s research is pivotal for enabling robust perception in autonomous systems, where incomplete data can lead to failures. Her work stands out for its elegant integration of geometric reasoning with modern deep learning, offering a scalable solution for real-world 3D understanding. As her citation count grows, Whitelaw is poised to become a key figure in shaping how machines perceive and interact with three-dimensional environments.
Research Focus
Key Achievements
Top Papers
- 1