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depth estimation

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.

Computer, Electrical and Mathematical Sciences and Engineering (CEMSE)

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