Model Reprogramming for Low-Level Image Processing

Model reprogramming [1] or input visual prompts [2] has been successfully used in reusing pretrained image classifiers. This project aims to explore whether model reprogramming can enable the transferability of pretrained deep neural networks across low-level image processing tasks. Specifically, we will investigate the feasibility of using pretrained models (e.g., U-Net) for image denoising, enhancement, and super-resolution on different tasks by introducing task-specific visual prompts.

[1] Pin-Yu Chen. Model reprogramming: Resource-efficient cross-domain machine learning. In AAAI, 2024.

[2] Aochuan Chen, Yuguang Yao, Pin-Yu Chen, Yihua Zhang, and Sijia Liu. Understanding and improving visual prompting: A label-mapping perspective. In CVPR, 2023.

Supervisor: Feng Liu