PaAgent: Portrait-Aware Image Restoration Agent via Subjective-Objective Reinforcement Learning
Image Restoration (IR) agents, leveraging multimodal large language models to perceive degradation and invoke restoration tools, have shown promise in automating IR tasks. However, existing IR agents typically lack an insight summarization mechanism for past interactions, which results in an exhaustive search for the optimal IR tool. To address this limitation, we propose a portrait-aware IR agent, dubbed PaAgent, which incorporates a self-evolving portrait bank for IR tools and Retrieval-Augmented Generation (RAG) to select a suitable IR tool for input. Specifically, to construct and evolve the portrait bank, the PaAgent continuously enriches it by summarizing the characteristics of vari...
| Authors | Yijian Wang, Qingsen Yan, Jiantao Zhou et al. |
|---|---|
| Primary category | cs.CV |
| Published | 17 March 2026 |
| Last updated at source | 17 March 2026 |
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