Utsav Kumar
Papers
1
Total Citations
3
H-Index
1
About
Utsav Kumar is a computer vision researcher whose work focuses on advancing real-time 3D object detection and spatial understanding for autonomous systems. His most-cited paper, "Real-Time 3D Bounding Box Estimation with RCNN-Resnet101 and Adaptive Projection Matrices" (2024), introduces a novel method that combines a Region-Based Convolutional Neural Network (RCNN) with a ResNet-101 backbone and adaptive projection matrices to achieve accurate 3D bounding box estimation in real time. This contribution directly addresses critical challenges in autonomous driving, robotics, and augmented reality, where precise spatial perception is essential for safe and efficient operation. By optimizing the balance between computational speed and detection accuracy, Kumar’s work enables more reliable object localization in dynamic environments. With 3 citations in its first year, the paper is gaining early recognition for its practical impact. Kumar’s research sits at the intersection of deep learning and geometric computer vision, and his adaptive projection approach represents a meaningful step toward bridging the gap between 2D image data and 3D world coordinates. His work continues to influence the development of efficient, deployable perception systems for real-world applications.
Research Focus
Key Achievements
Top Papers
- 1