AI RESEARCH
SRNeRV: A Scale-wise Recursive Framework for Neural Video Representation
arXiv CS.CV
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ArXi:2603.08227v1 Announce Type: new Implicit Neural Representations (INRs) have emerged as a promising paradigm for video representation and compression. However, existing multi-scale INR generators often suffer from significant parameter redundancy by stacking independent processing blocks for each scale. Inspired by the principle of scale self-similarity in the generation process, we propose SRNeRV, a novel scale-wise recursive framework that replaces this stacked design with a parameter-efficient shared architecture.