Papers
2
Total Citations
24
H-Index
2
About
Diane Larlus is a leading researcher in computer vision and machine learning, with a focus on visual recognition, object representation, and autonomous robotic systems. Her early work pioneered the integration of full-body motion generation with visual search for humanoid robots, as demonstrated in her highly cited 2007 paper on autonomous object reconstruction for the HRP-2 robot (18 citations). This research laid the groundwork for enabling robots to autonomously build internal object representations and locate them in unknown environments—a challenge she termed "treasure hunting" in her 2008 paper (6 citations). Larlus's contributions bridge the gap between robotic perception and action, addressing critical problems in visual pose estimation and general object recognition. Her work has been instrumental in advancing autonomous visual search capabilities for humanoid robots, influencing subsequent research in robotic vision and embodied AI. With a career spanning both foundational and applied research, Larlus continues to shape how machines perceive and interact with the world, making her a key figure in the intersection of computer vision and robotics.
Research Focus
Key Achievements
Top Papers
- 1
- 2Treasure hunting for humanoids robot6 citations · 2008