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Foundation Models and 3D Computer Vision
Srinath Sridhar
Thursday, May 25, 2023, 11:00 am-12:00 pm Calendar
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Abstract

In this partly speculative talk, I will share my thoughts on Foundation Models (aka Large Models) and their implications for object-centric 3D computer vision. To do this, I will first discuss some of our recent work on learning to generate, edit, arrange, and capture 3D objects and humans. This will include our work on (1) recursively generating and modifying 3D shapes using natural language descriptions; (2) arranging 3D shapes and re-arranging collections of shapes; and (3) capturing real-world objects and human hands. Next, using our and others' work as examples, I will speculate on how Foundation Models could provide new perspectives for addressing the same problems. I will conclude by identifying open opportunities and challenges.

Bio

Srinath Sridhar (https://srinathsridhar.com) is an assistant professor of computer science at Brown University. He received his PhD at the Max Planck Institute for Informatics and was subsequently a postdoctoral researcher at Stanford. His research interests are in 3D computer vision and machine learning. Specifically, his group focuses on visual understanding of 3D human physical interactions with applications ranging from robotics to mixed reality. He is a recipient of the NSF CAREER award, Google Research Scholar award, and his work received the Eurographics Best Paper Honorable Mention. He spends part of his time as a visiting academic at Amazon Robotics and has previously spent time at Microsoft Research Redmond and Honda Research Institute.

This talk is organized by Samuel Malede Zewdu