Anush Kumar

Papers

Total Citations

H-Index

About

Anush Kumar is a rising researcher in computer vision and robotics, with a focus on robust geometric perception for autonomous systems. His work tackles the practical challenge of maintaining accurate stereo vision in real-world, dynamic environments—a problem often overlooked in controlled laboratory settings. In his notable 2024 paper, "Flow-Guided Online Stereo Rectification for Wide Baseline Stereo," Kumar addresses the critical issue of constant re-calibration required by autonomous vehicles and robots exposed to environmental factors like vibration and structural stress. By leveraging optical flow to guide online rectification, he proposes a solution that adapts to wide baseline configurations without manual intervention. Though early in his career, his work has already garnered attention, with his most-cited paper accumulating 3 citations. Kumar’s contributions are particularly significant for advancing the reliability of perception systems in field robotics and autonomous navigation, where traditional stereo rectification assumptions break down. His research promises to enhance the resilience of computer vision systems operating in-the-wild, marking him as a promising voice in the next generation of geometric computer vision researchers.