AI RESEARCH
Frames2Residual: Spatiotemporal Decoupling for Self-Supervised Video Denoising
arXiv CS.CV
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ArXi:2603.10417v1 Announce Type: new Self-supervised video denoising methods typically extend image-based frameworks into the temporal dimension, yet they often struggle to integrate inter-frame temporal consistency with intra-frame spatial specificity. Existing Video Blind-Spot Networks (BSNs) require noise independence by masking the center pixel, this constraint prevents the use of spatial evidence for texture recovery, thereby severing spatiotemporal correlations and causing texture loss.