People communicate about objects, scenes, and spatial relations in the real world using natural language. In this talk, I will give an overview of recent work that explores how to endow computational systems with the ability to connect natural language and 3D representations. Concretely, I will summarize projects that develop neural models for localizing and describing objects in 3D scenes using natural language, generating 3D content from text, and other recent work exploring tasks that require connections between natural language and 3D representations.

Angel Chang is an Assistant Professor at Simon Fraser University and a Canada CIFAR AI Chair with Amii. Her research connects language to visual and 3D representations, and grounds language for embodied agents in indoor environments. She has worked on synthesizing 3D scenes and shapes from natural language, as well as localizing objects in 3D.  Her work has been recognized by awards such as the SGP dataset award for ShapeNet and ScanNet.