Active Sampling for Ultra-Low-Bit-Rate Video Compression via Conditional Controlled Diffusion
Diffusion models provide a powerful generative prior for perceptual reconstruction at ultra-low bitrates, but effective video compression requires controlling the generative process using highly compact conditioning signals. In this work, we present ActDiff-VC, a diffusion-based video compression framework for the ultra-low-bitrate regime. Our method partitions videos into variable-length segments, transmits keyframes only when needed, and summarizes temporal dynamics using a compact set of tracked point trajectories. Conditioned on these sparse signals, a conditional diffusion decoder synthesizes the remaining frames, enabling perceptually realistic reconstruction under severe rate const...
| Authors | Amirhosein Javadi, Shirin Saeedi Bidokhti, Tara Javidi |
|---|---|
| Primary category | cs.CV |
| Published | 4 May 2026 |
| Last updated at source | 1 October 2026 |
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