CineScale: Tuning-Free High-Resolution Video Generation

arXiv:2508.15774 · cs.CV · Submitted 2025-08-21 · Read on arXiv

cs.CV

Submitted: 2025-08-21

Updated: 2026-09-16

Code: https://github.com/Eyeline-Labs/CineScale

Project page: https://eyeline-labs.github.io/CineScale

Terminology

• Diffusion Model — 35× in this paper · explained in 8 episodes
• Diffusion Models — 33× in this paper · explained in 6 episodes
• Fidelity — 15× in this paper · explained in 2 episodes
• Transformer — 7× in this paper · explained in 2 episodes
• Consistency — 6× in this paper · explained in 3 episodes
• Fine-Tuning — 6× in this paper · explained in 5 episodes
• Generative Model — 4× in this paper · explained in 2 episodes
• Generative Models — 4× in this paper · explained in 2 episodes
• Latent Representation — 3× in this paper · explained in 2 episodes
• Ablation — 2× in this paper · explained in 1 episode
• Attention Mechanism — 2× in this paper · explained in 3 episodes
• Benchmark — 2× in this paper · explained in 2 episodes
• Failure Modes — 2× in this paper · explained in 3 episodes
• Flow Matching — 2× in this paper · explained in 8 episodes
• Latent Diffusion Model — 2× in this paper · explained in 2 episodes
• Latent Diffusion Models — 2× in this paper · explained in 2 episodes
• Sparse Attention — 2× in this paper · explained in 5 episodes
• Adam — 1× in this paper · explained in 2 episodes
• Adaptation — 1× in this paper · explained in 1 episode
• Alignment — 1× in this paper · explained in 1 episode
• Core — 1× in this paper · explained in 2 episodes
• Distribution Shift — 1× in this paper · explained in 6 episodes
• Embeddings — 1× in this paper · explained in 2 episodes
• Generative Modeling — 1× in this paper · explained in 3 episodes
• Latent Space — 1× in this paper · explained in 7 episodes
• LoRA Fine-Tuning — 1× in this paper · explained in 3 episodes
• Temporal Reasoning — 1× in this paper · explained in 2 episodes
• Transformer Architecture — 1× in this paper · explained in 2 episodes

Sources

• VideoCrafter1: Open Diffusion Models for High-Quality Video Generation
• Extending Context Window of Large Language Models via Positional Interpolation
• Make a Cheap Scaling: A Self-Cascade Diffusion Model for Higher-Resolution Adaptation
• LTX-Video: Realtime Video Latent Diffusion
• Latent Video Diffusion Models for High-Fidelity Long Video Generation
• FouriScale: A Frequency Perspective on Training-Free High-Resolution Image Synthesis
• MultiDiffusion: Fusing Diffusion Paths for Controlled Image Generation
• Stable Video Diffusion: Scaling Latent Video Diffusion Models to Large Datasets
• Wan: Open and Advanced Large-Scale Video Generative Models
• UltraVideo: High-Quality UHD Video Dataset with Comprehensive Captions
• CogVideoX: Text-to-Video Diffusion Models with An Expert Transformer
• LUVE : Latent-Cascaded Ultra-High-Resolution Video Generation with Dual Frequency Experts
• VBench: Comprehensive Benchmark Suite for Video Generative Models
• VBench++: Comprehensive and Versatile Benchmark Suite for Video Generative Models
• Pyramidal Flow Matching for Efficient Video Generative Modeling
• HunyuanVideo: A Systematic Framework For Large Video Generative Models
• YaRN: Efficient Context Window Extension of Large Language Models
• SDXL: Improving Latent Diffusion Models for High-Resolution Image Synthesis

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