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Computer, Electrical and Mathematical Sciences and Engineering
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egocentric video

Yuqian Fu

Postdoctoral Research Fellow, Computer Science

egocentric video Video Understanding Long-Form Video Understanding multimodal AI few-shot learning

Yuqian Fu's research topics are computer vision and deep learning. She mainly aims to build more generalizable vision models by addressing challenges that arise when applying them to downstream tasks,
KAUST-CEMSE-CS-PhD-Dissertation-Defense-Toward-Robust-Multimodal-Egocentric

Toward Robust Multimodal Egocentric Video Understanding

Merey Ramazanova, Postdoctoral Research Fellow, Computer Science
Jul 28, 17:00 - 17:45

B4 L5 R5209; Zoom Meeting 92591807769

egocentric video Multimodal learning robust modeling

This thesis advances egocentric video understanding through multimodal learning, large-scale dataset development, and robust adaptation techniques; it introduces new models, benchmarks, and methods for building scalable, resilient perception systems that operate effectively in real-world, first-person environments.

Computer, Electrical and Mathematical Sciences and Engineering (CEMSE)

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