GS-STVSR achieves state-of-the-art continuous spatio-temporal video super-resolution quality with nearly constant inference time at standard scales and over 3x speedup at extreme scales using 2D Gaussian Splatting.
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Flashvsr: Towards real- time diffusion-based streaming video super-resolution
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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.
LumaFlux is a physically and perceptually guided diffusion transformer for SDR-to-HDR conversion that introduces PGA, PCM, and HDR Residual Coupler modules plus a new training corpus and benchmark, outperforming prior ITM methods.
OSDEnhancer delivers state-of-the-art real-world space-time video super-resolution via one-step diffusion with temporal coherence and texture enrichment LoRAs plus a deformable recurrent VAE decoder.
Stream-DiffVSR enables practical low-latency video super-resolution by combining a four-step distilled denoiser, auto-regressive temporal guidance, and a temporal processor in a strictly causal pipeline.
SmartDirector generates cinematic videos via Director-Gen for low-res keyframe-conditioned output followed by Director-SR refinement using high-res keyframes, trained on curated movie sequences.
AtlasVid proposes a decoupled global-local diffusion framework that trains at low resolution with LoRA and generalizes to ultra-high-resolution long video synthesis via semantic proxy guidance and locality-preserving attention.
FashionChameleon achieves interactive multi-garment video customization at 23.8 FPS via in-context teacher models, streaming distillation, and training-free KV cache rescheduling while using only single-garment data.
DiffST delivers state-of-the-art real-world space-time video super-resolution with 17x faster inference than prior diffusion methods by using one-step sampling, cross-frame context aggregation, and video representation guidance.
BurstGP enhances raw burst image super-resolution by integrating pretrained video diffusion priors through a multiframe-aware model, degradation-aware conditioning, and color-space conversion, outperforming prior methods on perceptual metrics.
DVFace uses a spatio-temporal dual-codebook and asymmetric fusion in a one-step diffusion model to deliver better video face restoration quality, temporal consistency, and identity preservation than recent methods.
Rein3D generates photorealistic, globally consistent 3D indoor scenes by using a restore-and-refine process where radial panoramic videos are restored via diffusion models and then used to update a 3D Gaussian field.
DiffHDR converts LDR videos to HDR by formulating the task as generative radiance inpainting in a video diffusion model's latent space, using Log-Gamma encoding and synthesized training data to achieve better fidelity and stability than prior methods.
SATB-VR trains few-step video restoration diffusion models via SNR-aware trajectory blending of predictor outputs with ground-truth and a denoiser-driven consistency loss to achieve favorable performance on benchmarks.
PixelWizard decouples global structure from fine details via a spatiotemporal anchor and introduces Noise-Span Aligned Shortcut Training with biased sampling to achieve over 10x faster sampling for high-fidelity 2K/4K video generation.
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.
DTI reformulates generative face video super-resolution as directional restoration using enhancement-and-injection conditioning and an SNR-aligned discriminative guide for dynamic sampling initialization, claiming SOTA performance.
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