Beyond Spatial-Domain Supervision: A Relation Constrained Space for Multi-Modal Image Fusion

arXiv:2609.38968 · cs.CV · Submitted 2026-09-30 · Read on arXiv

cs.CV

Submitted: 2026-09-30

Updated: 2026-09-30

Comments: Accepted to NeurIPS 2026

Code: https://github.com/GMY628/RCS-Fusion

License: http://arxiv.org/licenses/nonexclusive-distrib/1.0/

Terminology

• Transformer — 39× in this paper · explained in 2 episodes
• Relation-Constrained Supervision — 23× in this paper
• Alignment — 8× in this paper · explained in 1 episode
• Ablation — 7× in this paper · explained in 1 episode
• Multi-modal Image Fusion — 6× in this paper
• Contrastive Learning — 5× in this paper · explained in 5 episodes
• Relation Reasoning Module — 5× in this paper
• Ablation study — 4× in this paper · explained in 1 episode
• Feature Alignment Module — 4× in this paper
• Consistency — 3× in this paper · explained in 3 episodes
• Diffusion Model — 3× in this paper · explained in 8 episodes
• Cosine Similarity — 2× in this paper · explained in 3 episodes
• Downstream Tasks — 2× in this paper · explained in 2 episodes
• Feature Extraction — 2× in this paper · explained in 2 episodes
• Fidelity — 2× in this paper · explained in 2 episodes
• Representation Learning — 2× in this paper · explained in 2 episodes
• Ablation Studies — 1× in this paper · explained in 1 episode
• Adaptation — 1× in this paper · explained in 1 episode
• Aggregation — 1× in this paper · explained in 1 episode
• Alternating Optimization Scheme — 1× in this paper · explained in 1 episode
• Benchmark — 1× in this paper · explained in 2 episodes
• Computational overhead — 1× in this paper · explained in 2 episodes
• Core — 1× in this paper · explained in 2 episodes
• Fine-Tuning — 1× in this paper · explained in 5 episodes
• Generalizability — 1× in this paper · explained in 6 episodes
• Meta-learning — 1× in this paper · explained in 2 episodes
• Multi-level Features Adapter — 1× in this paper
• Score Function — 1× in this paper · explained in 4 episodes
• Transferability — 1× in this paper · explained in 4 episodes

Sources

• DINOv2: Learning Robust Visual Features without Supervision
• YOLOv12: Attention-Centric Real-Time Object Detectors
• Multi-Modal Image Fusion via Intervention-Stable Feature Learning
• Customized Fusion: A Closed-Loop Dynamic Network for Adaptive Multi-Task-Aware Infrared-Visible Image Fusion
• Image Fusion via Vision-Language Model
• DIDFuse: Deep Image Decomposition for Infrared and Visible Image Fusion

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