AI RESEARCH

FAPE-IR: Frequency-Aware Planning and Execution Framework for All-in-One Image Restoration

arXiv CS.AI

ArXi:2511.14099v3 Announce Type: replace-cross All-in-One Image Restoration (AIO-IR) aims to develop a unified model that can handle multiple degradations under complex conditions. However, existing methods often rely on task-specific designs or latent routing strategies, making it hard to adapt to real-world scenarios with various degradations. We propose FAPE-IR, a Frequency-Aware Planning and Execution framework for image restoration. It uses a frozen Multimodal Large Language Model (MLLM) as a planner to analyze degraded images and generate concise, frequency-aware restoration plans.