Akshat Gupta
Papers
1
Total Citations
2
H-Index
1
About
Akshat Gupta is a researcher at the forefront of robotics and computer vision, with a primary focus on enabling robots to autonomously build 3D models of previously unseen objects. His key research areas include active learning, neural radiance fields (NeRF), and robotic manipulation. Gupta’s major contribution is the development of ActNeRF, an uncertainty-aware active learning framework that allows a robot to efficiently construct complete 3D object representations by strategically selecting visual and re-orientation actions. This work addresses the critical challenge of occluded surfaces in object manipulation, demonstrating how physical interaction can rapidly fill gaps in a model. With 2 citations since its 2024 publication, ActNeRF represents a novel integration of active perception and manipulation, showcasing Gupta’s ability to tackle fundamental problems in embodied AI. His research is particularly notable for its practical implications in real-world robotic systems, where rapid adaptation to new objects is essential. For students and researchers, Gupta’s work offers a compelling example of how combining uncertainty estimation with interactive exploration can push the boundaries of robot learning and scene understanding.
Research Focus
Key Achievements
Top Papers
- 1