April 19, 2024, 4:45 a.m. | Yiran Xu, Taesung Park, Richard Zhang, Yang Zhou, Eli Shechtman, Feng Liu, Jia-Bin Huang, Difan Liu

cs.CV updates on arXiv.org arxiv.org

arXiv:2404.12388v1 Announce Type: new
Abstract: Video super-resolution (VSR) approaches have shown impressive temporal consistency in upsampled videos. However, these approaches tend to generate blurrier results than their image counterparts as they are limited in their generative capability. This raises a fundamental question: can we extend the success of a generative image upsampler to the VSR task while preserving the temporal consistency? We introduce VideoGigaGAN, a new generative VSR model that can produce videos with high-frequency details and temporal consistency. VideoGigaGAN …

abstract arxiv capability cs.cv fundamental generate generative however image question raises resolution results success temporal type video videos

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