Harsh Agrawal

Papers

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About

Harsh Agrawal is a researcher advancing the field of 3D computer vision, with a primary focus on novel-view synthesis for indoor scenes. His most notable contribution is the development of a simple yet highly effective framework for generating immersive, 3D-consistent indoor environments from just one or a few input images. This work, which has accumulated over 20 citations, addresses a critical challenge: producing high-resolution images and videos from viewpoints that extrapolate far beyond the original captures, all while maintaining structural coherence. By prioritizing simplicity and effectiveness over complex, often brittle, existing methods, Agrawal’s approach has the potential to democratize 3D scene synthesis for applications in virtual reality, robotics, and architectural visualization. His research demonstrates a keen ability to solve fundamental problems in 3D reconstruction, making it easier to create realistic, navigable digital twins of real-world spaces. With his work already influencing the field, Harsh Agrawal is a promising voice in the ongoing effort to bridge the gap between sparse visual data and rich, interactive 3D experiences.