Kishaan Jeeveswaran
Papers
1
Total Citations
5
H-Index
1
About
Kishaan Jeeveswaran is a rising researcher in computer vision, specializing in self-supervised learning for 3D scene understanding. His work centers on monocular depth estimation—a critical task for enabling machines to perceive depth from a single camera without expensive labeled data. In his most cited paper, "Image Masking for Robust Self-Supervised Monocular Depth Estimation" (2023, 5 citations), Jeeveswaran tackles a key challenge: improving the robustness and accuracy of depth predictions by masking problematic image regions during training. This approach enhances the model’s ability to handle occlusions and dynamic objects, advancing the state of the art in joint depth and ego-motion estimation. While still early in his career, his contributions are gaining recognition for their practical impact on autonomous navigation and robotics. Jeeveswaran’s work exemplifies how clever data augmentation strategies can push self-supervised methods closer to the reliability of supervised approaches, making him a promising voice in the field of geometric computer vision.
Research Focus
Key Achievements
Top Papers
- 1Image Masking for Robust Self-Supervised Monocular Depth Estimation5 citations · 2023