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An Intelligent Agentic System for Complex Image Restoration Problems
Kaiwen Zhu, Jinjin Gu, Zhiyuan You +2
Real-world image restoration (IR) is inherently complex and often requires combining multiple specialized models to address diverse degradations. Inspired by human problem-solving,…
A Preliminary Exploration Towards General Image Restoration
Xiangtao Kong, Jinjin Gu, Yihao Liu +4
Despite the tremendous success of deep models in various individual image restoration tasks, there are at least two major technical challenges preventing these works from being app…
Interpreting Low-level Vision Models with Causal Effect Maps
Jinfan Hu, Jinjin Gu, Shiyao Yu +5
Deep neural networks have significantly improved the performance of low-level vision tasks but also increased the difficulty of interpretability. A deep understanding of deep model…
LM4LV: A Frozen Large Language Model for Low-level Vision Tasks
Boyang Zheng, Jinjin Gu, Shijun Li +1
The success of large language models (LLMs) has fostered a new research trend of multi-modality large language models (MLLMs), which changes the paradigm of various fields in compu…
Enhancing Descriptive Image Quality Assessment with A Large-scale Multi-modal Dataset
Zhiyuan You, Jinjin Gu, Xin Cai +4
With the rapid advancement of Vision Language Models (VLMs), VLM-based Image Quality Assessment (IQA) seeks to describe image quality linguistically to align with human expression…
Scaling Up to Excellence: Practicing Model Scaling for Photo-Realistic Image Restoration In the Wild
Fanghua Yu, Jinjin Gu, Zheyuan Li +6
We introduce SUPIR (Scaling-UP Image Restoration), a groundbreaking image restoration method that harnesses generative prior and the power of model scaling up. Leveraging multi-mod…