CVPR Daily - Tuesday

DAILY T u e s d a y Learn3dgen 27 based, reasoning systems (also known as Type I ) and reflexive , neural network- based systems ( Type II systems) and agreed that maybe not all events need be present in datasets as long as we can adaptively employ Type I system reasoning to make inferences about unusual scenarios. Everyone agreed that the topics covered in the workshop are incredibly important to work on for making progress in advancing AI and enhancing computational tools to support human creativity . Angel Xuan Chang is an Assistant Professor of Computer Science at Simon Fraser University. Angel’s research focuses on the intersection of natural language understanding, computer graphics, and AI. Her research connects language to 3D representations of shapes and scenes and addresses grounding of language for embodied agents in indoor environments. She has worked on methods for synthesizing 3D scenes and shapes, 3D scene understanding, and helped to create various datasets for 3D deep learning (ShapeNet, ScanNet, Matterport3D). She received her Ph.D. in Computer Science from Stanford, under the supervision of Chris Manning. She is a recipient of the TUM-IAS Hans Fischer Fellowship and a Canada CIFAR AI Chair. Angel’s Bio