ControlFusion: A Controllable Image Fusion Network with Language-Vision Degradation Prompts

NeurIPSOral2025

Authors
Linfeng Tang, Yeda Wang, Zhanchuan Cai, Junjun Jiang, Jiayi Ma
Affiliation
Wuhan University
Venue
NeurIPS 2025
Track
Oral

TL;DR

Current image fusion methods struggle with real-world composite degradations and lack the flexibility to accommodate user-specific needs. To address this, we propose ControlFusion, a controllable fusion network guided by language-vision prompts that adaptively mitigates composite degradations.

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Topics

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