3D understanding

Geometry-Aware Visual Understanding and Stereoscopic Video Generation

Jian Shi, Ph.D. Student, Computer Science

Oct 26, 03:00 - 05:00

B1 R2202

3D understanding 3D reconstruction geometry modeling stereo video synthesis generative ai

This thesis develops a geometry-aware dissolving transformation that selectively removes unnecessary fine-grained visual and geometric detail while preserving coarse structural information, to achieve more robust representation learning, higher-quality stereoscopic video synthesis, and more efficient multi-view geometry processing.

Jian Shi

Ph.D. Student, Computer Science

3D understanding generative ai immersive technologies stereo video synthesis 3D reconstruction

Jian Shi 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, geometric deep learning, generative AI, and 3D visual computing, with particular emphasis on stereo video synthesis, 3D perception, scene reconstruction, and immersive visual experiences.

Silvio Giancola

Research Scientist, Image and Video Understanding Lab

Computer Vision artificial intelligence Technology Transfer Deep learning 3D understanding Sports start-up robotics

Silvio Giancola is a Research Scientist at King Abdullah University of Science and Technology (KAUST), under the supervision of Prof. Bernard Ghanem in the Image and Video Understanding Laboratory (IVUL), part of the Center of Excellence for Generative AI (GenAI).