6 papers
How far have we gone in Generative Image Restoration? A study on its capability, limitations and evaluation practices
Xiang Yin, Jinfan Hu, Zhiyuan You +4
Generative Image Restoration (GIR) has achieved impressive perceptual realism, but how far have its practical capabilities truly advanced compared with previous methods? To answer…
Position: Evaluation of Visual Processing Should Be Human-Centered, Not Metric-Centered
Jinfan Hu, Fanghua Yu, Zhiyuan You +5
This position paper argues that the evaluation of modern visual processing systems should no longer be driven primarily by single-metric image quality assessment benchmarks, partic…
Revisiting the Generalization Problem of Low-level Vision Models Through the Lens of Image Deraining
Jinfan Hu, Zhiyuan You, Jinjin Gu +3
Generalization to unseen degradations remains a fundamental challenge for low-level vision models. This paper aims to investigate the underlying mechanism of this failure, using im…
Harnessing Diffusion-Yielded Score Priors for Image Restoration
Xinqi Lin, Fanghua Yu, Jinfan Hu +5
Deep image restoration models aim to learn a mapping from degraded image space to natural image space. However, they face several critical challenges: removing degradation, generat…
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…
UniCon: Unidirectional Information Flow for Effective Control of Large-Scale Diffusion Models
Fanghua Yu, Jinjin Gu, Jinfan Hu +2
We introduce UniCon, a novel architecture designed to enhance control and efficiency in training adapters for large-scale diffusion models. Unlike existing methods that rely on bid…