Keshav Gupta

Hi, I am an MSCS student in the CSE Department at UC San Diego.

I completed my B.Tech in Computer Science with Honours in Computer Vision at IIIT Hyderabad, where I was advised by Dr. Ravi Kiran in the mobility group. We primarily focused on perception-driven computer vision algorithms, with an emphasis on dashcam-based applications.

I have worked in the Center for Visual Information and Technology (CVIT) on several projects in Computer Vision concerning perception. I also worked at the Robotics Research Center (RRC) under Dr. Madhava Krishna where I worked on perception in autonomous driving. I also worked at the Machine Learning Lab (MLL) with Dr. Charu Sharma and Dr. Avinash Sharma where I researched on 3D Gaussian Splatting compression.

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My research interests lie in the field of Computer Vision and Robotics, with a focus on perception for autonomous systems. I am particularly interested in developing algorithms that enable robots to understand and interact with their environment effectively.

Diffusion-FS is a self-supervised approach for freespace prediction using monocular camera images. It takes in a dataset of raw driving logs containing image and ego trajectory pairs and processes such an unannotated dataset to generate free-space segments essential for autonomous driving.

We propose a novel Segmentation and Cross-Association (SAC) module and a robust cross-association-based tracking algorithm optimized for the simultaneous presence of riders and motorcycles. We also introduce the RideSafe-400 dataset, a comprehensive annotated dashcam video dataset for triple riding and helmet rule violations.