AI RESEARCH
NeR-SC: Adapting Neural Video Representation to Screen Content
arXiv CS.CV
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ArXi:2605.27024v1 Announce Type: new Implicit neural representations have emerged as a promising paradigm for video compression, with recent methods achieving competitive performance on natural video. However, screen content video -- common in remote desktop, online education, and cloud gaming -- exhibits distinct statistics: sharp edges, limited color palettes, and strong temporal redundancy. Existing neural representation methods, designed for natural scenes, lack mechanisms to exploit these properties, leaving substantial room for improvement.