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NeurIPS 2026Dalian MinzuTsinghuaUnified multimodal models

When Integral Meets Decomposition: A Signal-Level Self-Supervised Feature Decompose Paradigm for Multi-Modal Image Fusion

A signal-level self-supervised paradigm reformulates multimodal feature decomposition via 1D integral constraints, achieving state-of-the-art fusion performance without ground-truth feature maps.

Zeyu Wang, Jiayu Wang, Haiyu Song, Haoran Duan

Sydney Poster Session 5, Thu, Dec 10, 10:00 AM–1:00 PM, Hall 1-4 · Published 2026

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lenient 2/5
medium 5/10
strict 0/5
74%Highly rated
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NeurIPS 2026Dalian MinzuTsinghuaUnified multimodal models

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

Proposed relation-constrained supervision shifts multi-modal image fusion from spatial sources to a learned relation space via aligned DINO and CLIP features, improving results across backbones.

Zeyu Wang, Mingyu Ge, Haiyu Song, Haoran Duan

Sydney Poster Session 3, Wed, Dec 9, 10:00 AM–1:00 PM, Hall 1-4 · Published 2026

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9/20 AI panelreviewers recommend it

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AI panel: 9 of 20 reviewers recommend it
lenient 3/5
medium 6/10
strict 0/5