Professor Angela Dai (Technical University of Munich): “Building 3D Worlds from Imperfect Data”
Speaker: Professor Angela Dai (Technical University of Munich)
Title: Building 3D Worlds from Imperfect Data
Video:
Abstract: Our observations of the world are always incomplete. Images and range sensors capture only fragments of real environments, leaving significant portions of scenes unobserved. At the same time, many applications, ranging from simulation to embodied AI, require complete and structured models of the 3D world. In this talk, we explore approaches for learning generative models of 3D scenes from incomplete, imperfect real-world data. We examine how self-supervised formulations for scene completion can leverage visibility reasoning together with modern generative techniques such as flow matching to infer plausible geometry in unobserved regions of real scans. Building on geometric representations, we then develop methods for synthesizing realistic appearance conditioned on 3D structure, enabling large-scale generation of realistic 3D indoor spaces. Ultimately, usable 3D worlds must support interaction. To this end, we leverage image generative model priors to synthesize plausible human interactions within 3D scenes. Together, these ideas move toward generative 3D world models that can be complete, realistic, and interacted with.
Bio: Angela Dai is an Associate Professor at the Technical University of Munich where she leads the 3D AI Lab. Angela’s research aims to enable machines to understand, model, and generate real-world 3D environments. She focuses on enabling the creation of rich, semantically grounded, and interactable 3D worlds that allow machines not only to perceive physical spaces, but to reason about them and act within them. She received her PhD in computer science from Stanford in 2018, advised by Pat Hanrahan, and her BSE in computer science from Princeton in 2013. Her research has been recognized through an ECVA Young Researcher Award, ERC Starting Grant, Eurographics Young Researcher Award, German Pattern Recognition Award, Google Research Scholar Award, and an ACM SIGGRAPH Outstanding Doctoral Dissertation Honorable Mention. She has also served as Program Chair for Eurographics 2025 and CVPR 2026.
