Rohit Mohan
Papers
7
Total Citations
273
H-Index
5
About
Rohit Mohan is a computer vision and robotics researcher whose work sits at the intersection of scene understanding, autonomous navigation, and panoptic perception. His research primarily focuses on developing advanced segmentation and tracking frameworks that enable robots and autonomous vehicles to comprehensively interpret complex, dynamic environments. Mohan's most influential contribution, "Panoptic nuScenes," has garnered 183 citations and established a foundational large-scale benchmark for LiDAR-based panoptic segmentation and tracking — a critical capability for autonomous vehicles operating in urban settings. His work on "Amodal Panoptic Segmentation" (49 citations) broke new ground by teaching machines to reason about occluded objects, mimicking human perceptual cognition. Earlier work on "MOPT: Multi-Object Panoptic Tracking" (21 citations) demonstrated his commitment to unifying diverse perception tasks into cohesive frameworks rather than treating them in isolation. Beyond autonomous driving, Mohan has extended his expertise to indoor robot localization and healthcare robotics, as evidenced by his "Syn-Mediverse" dataset for intelligent scene understanding in medical facilities. Spanning multiple domains — from urban driving to hospital environments — his research reflects a broad, impactful vision of making autonomous systems truly perception-aware in the real world.
Research Focus
Key Achievements
Top Papers
- 1
- 2Amodal Panoptic Segmentation49 citations · 2022
- 3MOPT: Multi-Object Panoptic Tracking21 citations · 2020
- 4EfficientPS: Efficient Panoptic Segmentation7 citations · 2021
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