scene understanding

Modeling the Visual World Across Space and Time: From Observation to Interaction

Jinjie Mai , Ph.D. Student, Computer Science

Nov 19, 16:30 - 18:30

Zoom Meeting 3940614410

3D understanding scene understanding Computational modeling deep learning

This dissertation develops methods to recover and model the visual world consistently across space and time from images and video, enabling both accurate understanding of scene geometry and coherent, event-driven video editing grounded in user intent.

Advancing Monocular Depth Estimation: High-Resolution and Amodal Understanding

Zhenyu Li, Ph.D. Student, Computer Science

Nov 17, 15:00 - 17:00

B1 R2202

depth estimation geometric modeling computational imaging visual computing 3D reconstruction scene understanding Advanced Perception

This thesis advances monocular depth estimation to develop efficient methods for recovering fine geometric details, such as object boundaries and thin structures, from high-resolution images while preserving scene-wide consistency and metric scale.

Zhenyu Li

Ph.D. Student, Computer Science

3D reconstruction scene understanding depth estimation generative ai visual computing Advanced Perception

Zhenyu Li is a final-year Ph.D. candidate in Computer Science at King Abdullah University of Science and Technology (KAUST), where he is advised by Prof. Peter Wonka, specializing in computer vision, 3D vision, and generative AI, with particular emphasis on monocular depth estimation, high resolution 3D perception, and scene reconstruction.

Jinjie Mai

Ph.D. Student, Computer Science

scene understanding 3D understanding generative models deep learning machine learning Computer Vision

Jinjie Mai is a Ph.D. student in Computer Science at King Abdullah University of Science and Technology (KAUST), advised by Prof. Bernard Ghanem, where his research focuses on modeling the visual world across space and time from images and video, spanning computer vision, visual computing, and generative AI.