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ConFusion framework enables fine-grained controllable infrared-visible image fusion

By PulseAugur Editorial · [1 sources] ·

Researchers have developed ConFusion, a new framework for fine-grained controllable infrared and visible image fusion. This method learns a continuous fusion space using Gaussian-conditioned spatial-aware modulation, allowing for flexible integration of thermal and structural information. ConFusion utilizes a dual-branch architecture for disentangling representations and employs a multimodal large language model to interpret user intents into modulation variables for precise image fusion. Experiments indicate that ConFusion surpasses existing methods in both fusion quality and downstream task performance. AI

IMPACT Enables more precise and adaptable image fusion for downstream applications by leveraging LLMs for control.

RANK_REASON The item describes a new research paper detailing a novel framework for image fusion. [lever_c_demoted from research: ic=1 ai=1.0]

Read on Hugging Face Daily Papers →

AI-generated summary · Google Gemini · from 1 sources. How we write summaries →

ConFusion framework enables fine-grained controllable infrared-visible image fusion

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The item describes a new research paper detailing a novel framework for image fusion. [lever_c_demoted from research: ic=1 ai=1.0]
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COVERAGE [1]

  1. Hugging Face Daily Papers TIER_1 English(EN) ·

    ConFusion: Continuous Fusion Space Learning for Fine-Grained Controllable Infrared and Visible Image Fusion

    Controllable infrared-visible image fusion aims to integrate complementary thermal and structural information with flexible region-aware modulation, producing fused images that adapt to diverse user requirements and downstream tasks. However, existing methods typically rely on pr…

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