TurboVSR: Fantastic Video Upscalers and Where to Find Them

TL;DR

TurboVSR is an ultra-efficient diffusion-based video super-resolution model that significantly reduces processing time while maintaining high-quality results, enabling practical super-resolution of high-resolution videos.

Contribution

The paper introduces TurboVSR, combining high compression, factorized conditioning, and model shortcuts to achieve over 100x faster video super-resolution without sacrificing quality.

Findings

Achieves 100+ times faster processing than previous methods.

Maintains state-of-the-art quality in super-resolution tasks.

Supports ultra-high-resolution images up to 4K.

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.