From Pixels to Perception: Generative and Adaptive Methodologies for Degraded Visual Scenarios

The Hong Kong University of Science and Technology
Department of Computer Science and Engineering


PhD Thesis Defence


Title: "From Pixels to Perception: Generative and Adaptive Methodologies for
Degraded Visual Scenarios"

By

Mr. Qiang WEN


Abstract:

Enhancing images and videos in degraded visual scenarios is a vital task in
computer vision, with applications across diverse fields such as medical
imaging, robotics, and photography. Existing works have focused heavily on
improving pixel-level quality in the final enhanced images through techniques
like denoising, deblurring, and deraining. However, increasing evidence
shows that while these pixel-level enhancement methods produce visually
appealing results from human sense, they may not be optimal for
downstream-task perception, such as object detection and semantic
segmentation, which are essential for applications like robotics and
autonomous driving. In this thesis, we aim to explore image and video
enhancement from pixel-level enhancement or human sense to perception-level
enhancement tailored for downstream computer vision tasks. This will be
achieved by developing innovative enhancement systems leveraging cutting-edge
methodologies, such as generative models and domain adaptation.
Specifically, this thesis explores four representative tasks: waterdrop
removal for driving scenes in rainy scenarios, low-light image enhancement
with generative models, enhancing HDR imaging with joint denoising and
deblurring, adapting large multi-modal models to see and read in the dark.
With extensive experiments, it gradually highlights the distinction between
pixel-level enhancement for human sense and perception-level enhancement for
downstream computer vision tasks, providing a clearer direction for future
research on enhancement objectives.


Date:                   Monday, 19 January 2026

Time:                   1:00pm - 3:00pm

Venue:                  Room 3494
                        Lifts 25-26

Chairman:               Prof. James Yeong Liang THONG (ISOM)

Committee Members:      Dr. Qifeng CHEN (Supervisor)
                        Dr. May FUNG
                        Prof. Nevin ZHANG
                        Prof. Ling SHI (ECE)
                        Prof. Yinqiang ZHENG (UTokyo)