TurboVSR: Fantastic Video Upscalers and Where to Find Them

• URL: http://arxiv.org/abs/2506.23618v1
• Date: Mon, 30 Jun 2025 08:24:13 GMT
• Title: TurboVSR: Fantastic Video Upscalers and Where to Find Them
• Authors: Zhongdao Wang, Guodongfang Zhao, Jingjing Ren, Bailan Feng, Shifeng Zhang, Wenbo Li,
• Abstract summary: Diffusion-based generative models have demonstrated exceptional promise in the video super-resolution (VSR) task.<n>We present TurboVSR, an ultra-efficient diffusion-based video super-resolution model.<n>TurboVSR performs on par with state-of-the-art VSR methods, while being 100+ times faster, taking only 7 seconds to process a 2-second long 1080p video.
• Score: 33.83721799307721
• License: http://creativecommons.org/licenses/by/4.0/
• Abstract: Diffusion-based generative models have demonstrated exceptional promise in the video super-resolution (VSR) task, achieving a substantial advancement in detail generation relative to prior methods. However, these approaches face significant computational efficiency challenges. For instance, current techniques may require tens of minutes to super-resolve a mere 2-second, 1080p video. In this paper, we present TurboVSR, an ultra-efficient diffusion-based video super-resolution model. Our core design comprises three key aspects: (1) We employ an autoencoder with a high compression ratio of 32$\times$32$\times$8 to reduce the number of tokens. (2) Highly compressed latents pose substantial challenges for training. We introduce factorized conditioning to mitigate the learning complexity: we first learn to super-resolve the initial frame; subsequently, we condition the super-resolution of the remaining frames on the high-resolution initial frame and the low-resolution subsequent frames. (3) We convert the pre-trained diffusion model to a shortcut model to enable fewer sampling steps, further accelerating inference. As a result, TurboVSR performs on par with state-of-the-art VSR methods, while being 100+ times faster, taking only 7 seconds to process a 2-second long 1080p video. TurboVSR also supports image resolution by considering image as a one-frame video. Our efficient design makes SR beyond 1080p possible, results on 4K (3648$\times$2048) image SR show surprising fine details.

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