2nd Workshop on Scalable 3D Scene Generation and Geometric Scene Understanding

Angel Xuan Chang is an Associate Professor at Simon Fraser University. Prior to this, she was a visiting research scientist at Facebook AI Research and a research scientist at Eloquent Labs working on dialogue. She received my Ph.D. in Computer Science from Stanford, where she was part of the Natural Language Processing Group and advised by Chris Manning. Her research focuses on connecting language to 3D representations of shapes and scenes and grounding of language for embodied agents in indoor environments. She has worked on methods for synthesizing 3D scenes and shapes from natural language, and various datasets for 3D scene understanding. In general, she is interested in the semantics of shapes and scenes, the representation and acquisition of common sense knowledge, and reasoning using probabilistic models.

Title: Compositional scene generation.

Jia Deng is a Professor of Computer Science at Princeton University, where he directs the Princeton Vision & Learning Lab. He received his Ph.D. from Princeton and his B.Eng. from Tsinghua University, both in computer science. His research spans 3D vision, object and action recognition, and automated reasoning, with interests in per-pixel 3D reconstruction of real-world scenes, visual understanding of objects and interactions, and connections between automated theorem proving, NLP, and AutoML. He is a recipient of the Sloan Research Fellowship, the NSF CAREER Award, the ONR Young Investigator Award, the ICCV Marr Prize, the CVPR Test-of-Time Award, and two ECCV Best Paper Awards.

Title: Data-Centric Visual Learning via Procedural Synthetic Scenes

Kristen Grauman is a Professor at the University of Texas at Austin and a Research Director in Facebook AI Research (FAIR). Her research in computer vision and machine learning focuses on video, visual recognition, and action for perception or embodied AI. She and her collaborators have been recognized with several Best Paper awards in computer vision, including a 2011 Marr Prize and a 2017 Helmholtz Prize (test of time award). She served for six years as an Associate Editor-in-Chief for the TPAMI and for ten years as an Editorial Board member for IJCV. She also served as a Program Chair of CVPR2015, NeurIPS2018, and ICCV2023.

Gim Hee Lee is an Associate Professor in the Department of Computer Science at the National University of Singapore (NUS). He received his PhD in Computer Science from ETH Zurich and was previously a researcher at Mitsubishi Electric Research Laboratories (MERL), USA. He has served as Area Chair for leading conferences such as CVPR, ICCV, ECCV, ICLR, and NeurIPS, and has held organizing roles including Program Chair of 3DV 2022, Demo Chair of CVPR 2023, and General Chair of 3DV 2025. He is a recipient of the Singapore NRF Investigatorship (Class of 2024). His research focuses on 3D computer vision and robotics.

Amir Zamir is an Assistant Professor of computer science at the Swiss Federal Institute of Technology (EPFL). His research is in computer vision and machine learning. Before joining EPFL in 2020, he was with UC Berkeley, Stanford, and UCF. He has received paper awards at SIGGRAPH 2022, CVPR 2020, CVPR 2018, CVPR 2016, and the NVIDIA Pioneering Research Award 2018, PAMI Everingham Prize 2022, and ECCV/ECVA Young Researcher Award 2022. His research has been covered by press outlets, such as The New York Times or Forbes. He was the chief scientist of Aurora Solar, a Forbes AI 50 company, from 2015 to 2022 and currently serves as the chief scientist of Duranta Inc.

Title: Multimodal Scene Understanding