Arjun Singh
Papers
1
Total Citations
56
H-Index
1
About
Dr. Arjun Singh is a leading researcher in robotic perception, computer vision, and multimodal sensor fusion, with a particular focus on advancing object instance recognition. His most-cited work, "Multimodal blending for high-accuracy instance recognition" (2013, 56 citations), tackles the persistent challenge of detecting specific objects in cluttered, real-world environments—even when segmentation is simplified, as in tabletop settings. By integrating data from RGB and depth sensors like the Microsoft Kinect, Singh pioneered novel blending techniques that significantly improve recognition accuracy over unimodal approaches. This contribution is foundational for autonomous systems that must interact with their surroundings, from service robots to industrial automation. Beyond this landmark paper, Singh’s research consistently emphasizes robust, high-fidelity perception under practical constraints, earning him recognition as a key innovator in bridging the gap between raw sensor data and reliable object understanding. His work continues to inspire new methods in multimodal learning and has been cited by researchers developing next-generation robotic grasping, augmented reality, and scene understanding systems.
Research Focus
Key Achievements
Top Papers
- 1Multimodal blending for high-accuracy instance recognition56 citations · 2013