DiffVC-OSD: One-Step Diffusion-based Perceptual Neural Video Compression Framework

• URL: http://arxiv.org/abs/2508.07682v1
• Date: Mon, 11 Aug 2025 06:59:23 GMT
• Title: DiffVC-OSD: One-Step Diffusion-based Perceptual Neural Video Compression Framework
• Authors: Wenzhuo Ma, Zhenzhong Chen,
• Abstract summary: We first propose DiffVC-OSD, a One-Step Diffusion-based Perceptual Neural Video Compression framework.<n>We employ an End-to-End Finetuning strategy to improve overall compression performance.
• Score: 45.134271969594614
• License: http://arxiv.org/licenses/nonexclusive-distrib/1.0/
• Abstract: In this work, we first propose DiffVC-OSD, a One-Step Diffusion-based Perceptual Neural Video Compression framework. Unlike conventional multi-step diffusion-based methods, DiffVC-OSD feeds the reconstructed latent representation directly into a One-Step Diffusion Model, enhancing perceptual quality through a single diffusion step guided by both temporal context and the latent itself. To better leverage temporal dependencies, we design a Temporal Context Adapter that encodes conditional inputs into multi-level features, offering more fine-grained guidance for the Denoising Unet. Additionally, we employ an End-to-End Finetuning strategy to improve overall compression performance. Extensive experiments demonstrate that DiffVC-OSD achieves state-of-the-art perceptual compression performance, offers about 20$\times$ faster decoding and a 86.92\% bitrate reduction compared to the corresponding multi-step diffusion-based variant.

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