Publicitários Criativos
Description: VideoGigaGAN
video super-resolution (2) videogigagan (1) temporal propogation (1)
Our model is able to upsample a video up to 8× with rich details.
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 tem
Our method only takes 15 minutes to optimize a representation from an in-the-wild video and can render novel views at 27 FPS. On the NVIDIA Dataset, our method achieves a rendering quality comparable to state-of-the-art NeRF-based methods but is much faster to train and render. * The bubble size in the figure indicates the training time (GPU-hours). The training time does not include preprocessing time for all methods.
Publicitários Criativos