Papers
15
Total Citations
332
H-Index
9
About
Hamid Rezatofighi is a prominent researcher at the intersection of computer vision, robotics, and human-centric scene understanding. His work is particularly distinguished by the development of the **JRDB ecosystem** — a comprehensive suite of datasets and benchmarks captured from the JackRabbot social mobile manipulator that has become a cornerstone resource for the robotics and computer vision communities. This flagship contribution, now cited over 117 times, enables researchers to study egocentric robot perception in real-world human environments through rich multimodal sensor data. Rezatofighi's research spans 3D pedestrian detection, multi-object tracking, social group dynamics, pose estimation, and object-level scene reconstruction. His JRDB-Act, JRDB-Pose, and JRDB-Social extensions demonstrate a sustained commitment to building holistic frameworks for understanding human behavior — from individual actions to complex group interactions — at scale. His work on systems like ODAM and MOLTR further advances 3D scene understanding for augmented reality and robotic applications. Collectively accumulating over 300 citations across a focused body of work, Rezatofighi has established himself as a key contributor to socially-aware robot perception, providing both foundational datasets and novel algorithmic solutions that meaningfully advance autonomous systems operating safely alongside humans.
Research Focus
Key Achievements
Top Papers
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- 4ODAM: Object Detection, Association, and Mapping using Posed RGB Video29 citations · 2021
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- 7JRMOT: A Real-Time 3D Multi-Object Tracker and a New Large-Scale Dataset17 citations · 2020
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- 9Real-Time Trajectory-Based Social Group Detection9 citations · 2023
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