MAVFusion: Efficient Infrared and Visible Video Fusion via Motion-Aware Sparse Interaction

MAVFusion: Efficient Infrared and Visible Video Fusion via Motion-Aware Sparse Interaction | Signal Canvas | ScienceToStartup

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Proof freshness: stale
Proof status: unverified
Display score: 7/10
Last proof check: 2026-04-03
Score updated: 2026-04-03
Score fresh until: 2026-05-03
References: 0
Source count: 0
Coverage: 67%

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source_context

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Evidence Receipt

Route status: building

Claims: 8

References: Pending verification

Proof: Verification pending

Freshness state: computing

Source paper: MAVFusion: Efficient Infrared and Visible Video Fusion via Motion-Aware Sparse Interaction

PDF: https://arxiv.org/pdf/2604.01958v1

Repository: https://github.com/ixilai/MAVFusion

Source count: Pending verification

Coverage: 67%

Last proof check: 2026-04-03T20:30:29.586Z

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Ready for execution: MAVFusion: Efficient Infrared and Visible Video Fusion via Motion-Aware Sparse Interaction

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Subject: MAVFusion: Efficient Infrared and Visible Video Fusion via Motion-Aware Sparse Interaction

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4/2/2026

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Claim map

Strong 8Mixed 0Weak 0

Evidencepartial
achieving a speed of 14.16 FPS at $640 \times 480$ resolution
Implicationpartial
Directly stated in abstract with specific numeric evidence
Verificationpartial
partial
Evidencepartial
Extensive experiments demonstrate that MAVFusion achieves state-of-the-art performance on multiple infrared and visible video benchmarks
Implicationpartial
Explicitly stated in abstract as a conclusion from extensive experiments
Verificationpartial
partial
Evidencepartial
we propose MAVFusion, an end-to-end video fusion framework featuring a motion-aware sparse interaction mechanism that enhances efficiency while maintaining superior fusion quality
Implicationpartial
Directly stated in abstract as a core feature of the proposed method
Verificationpartial
partial
Evidencepartial
Specifically, we leverage optical flow to identify dynamic regions in multi-modal sequences
Implicationpartial
Specifically described in abstract as a key technical component
Verificationpartial
partial
Evidencepartial
adaptively allocating computationally intensive cross-modal attention to these sparse areas to capture salient transitions and facilitate inter-modal information exchange
Implicationpartial
Directly stated in abstract as part of the method description
Verificationpartial
partial
Evidencepartial
For static background regions, a lightweight weak interaction module is employed to maintain structural and appearance integrity
Implicationpartial
Directly stated in abstract as part of the method description
Verificationpartial
partial
Evidencepartial
However, most existing methods are designed for static image fusion and cannot effectively handle frame-to-frame motion in videos
Implicationpartial
Stated as a limitation of existing methods in the abstract
Verificationpartial
partial
Evidencepartial
Current video fusion methods improve temporal consistency by introducing interactions across frames, but they often require high computational cost
Implicationpartial
Stated as a challenge in the abstract, though not quantified
Verificationpartial
partial

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MAVFusion: Efficient Infrared and Visible Video Fusion via Motion-Aware Sparse Interaction

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