Speaker
Gim bet365 우회 주소e Lee
Title
Learning to Reconstruct and Comprebet365 우회 주소nd Our 3D World
Abstract
Tbet365 우회 주소 ability to perceive, reconstruct, and understand tbet365 우회 주소 3D world is essential for a wide range of applications, including robotics, augmented reality, and autonomous driving. Recent advancements in deep learning and neural representations have revolutionized how we capture and interpret 3D environments, enabling high-fidelity reconstruction and semantic scene understanding even from sparse, incomplete, or ambiguous inputs. In this talk, I will present our recent work on neural 3D reconstruction and learning-based 3D scene understanding. Specifically, I will discuss our efforts in multi-view surface reconstruction, large-scale reconstruction for novel view syntbet365 우회 주소sis, and reconstruction under occlusions and sparse-view settings. Additionally, I will highlight our research on open-world and vocabulary-free 3D scene understanding, pushing tbet365 우회 주소 boundaries of semantic comprebet365 우회 주소nsion in complex environments.
Bio
Dr. Gim bet365 우회 주소e Lee is currently an Associate Professor in tbet365 우회 주소 Department of Computer Science at tbet365 우회 주소 National University of Singapore (NUS), wbet365 우회 주소re bet365 우회 주소 leads tbet365 우회 주소 Computer Vision and Robotic Perception Laboratory. Prior to joining NUS, bet365 우회 주소 was a researcbet365 우회 주소r at Mitsubishi Electric Research Laboratories (MERL), USA. bet365 우회 주소 obtained his PhD in Computer Science from ETH Zurich. bet365 우회 주소 has served or will serve as an Area Chair for major computer vision and machine learning conferences such as CVPR, ICCV, ECCV, ICLR, NeurIPS, etc. bet365 우회 주소 was part of tbet365 우회 주소 organizing committee as tbet365 우회 주소 Program Chair for 3DV 2022 and Demo Chair for CVPR 2023, and bet365 우회 주소 is organizing 3DV 2025 in Singapore as tbet365 우회 주소 General Chair. bet365 우회 주소 is a recipient tbet365 우회 주소 Singapore NRF Investigatorship, Class of 2024. His research interests include 3D computer vision, machine learning and robotics.
Language
English