A survey that groups efficient video diffusion methods into four paradigms—step distillation, efficient attention, model compression, and cache/trajectory optimization—and outlines open challenges for practical use.
arXiv preprint arXiv:2505.16239 (2025)
3 Pith papers cite this work. Polarity classification is still indexing.
fields
cs.CV 3years
2026 3verdicts
UNVERDICTED 3representative citing papers
MetaSR adaptively orchestrates metadata in a DiT-based generative SR model to deliver up to 1 dB PSNR gains and 50% bitrate savings across diverse content and degradations.
The NTIRE 2026 challenge releases the KwaiVIR benchmark for short-form UGC video restoration and reports strong results from 12 teams using generative models on both subjective and objective tracks.
citing papers explorer
-
Efficient Video Diffusion Models: Advancements and Challenges
A survey that groups efficient video diffusion methods into four paradigms—step distillation, efficient attention, model compression, and cache/trajectory optimization—and outlines open challenges for practical use.
-
MetaSR: Content-Adaptive Metadata Orchestration for Generative Super-Resolution
MetaSR adaptively orchestrates metadata in a DiT-based generative SR model to deliver up to 1 dB PSNR gains and 50% bitrate savings across diverse content and degradations.
-
NTIRE 2026 Challenge on Short-form UGC Video Restoration in the Wild with Generative Models: Datasets, Methods and Results
The NTIRE 2026 challenge releases the KwaiVIR benchmark for short-form UGC video restoration and reports strong results from 12 teams using generative models on both subjective and objective tracks.