Accelerating Video Diffusion via Training-Free Trajectory Routing

arXiv:2609.30096 · cs.CV, cs.AI · Submitted 2026-09-24 · Read on arXiv

cs.CV, cs.AI

Submitted: 2026-09-24

Updated: 2026-09-24

Terminology

• Consistency — 20× in this paper · explained in 3 episodes
• Calibration — 18× in this paper · explained in 7 episodes
• Diffusion Model — 18× in this paper · explained in 8 episodes
• Diffusion Models — 17× in this paper · explained in 6 episodes
• Distillation — 11× in this paper · explained in 2 episodes
• Conference on Computer Vision and Pattern Recognition — 7× in this paper
• Ablation — 5× in this paper · explained in 1 episode
• Fidelity — 5× in this paper · explained in 2 episodes
• Benchmark — 4× in this paper · explained in 2 episodes
• Latent Representation — 3× in this paper · explained in 2 episodes
• Transformer — 3× in this paper · explained in 2 episodes
• Winter Conference on Applications of Computer Vision — 3× in this paper
• Distribution Matching — 2× in this paper · explained in 2 episodes
• Generative Model — 2× in this paper · explained in 2 episodes
• Generative Models — 2× in this paper · explained in 2 episodes
• Latent Diffusion Model — 2× in this paper · explained in 2 episodes
• Latent Diffusion Models — 2× in this paper · explained in 2 episodes
• Prompt Adherence — 2× in this paper · explained in 2 episodes
• Redundancy — 2× in this paper · explained in 2 episodes
• Temporal consistency — 2× in this paper · explained in 2 episodes
• Accuracy — 1× in this paper · explained in 1 episode
• Adam — 1× in this paper · explained in 2 episodes
• Benchmarking — 1× in this paper · explained in 4 episodes
• Cooperation — 1× in this paper · explained in 2 episodes
• Generalization — 1× in this paper · explained in 13 episodes
• Latent Space — 1× in this paper · explained in 7 episodes
• Mode Collapse — 1× in this paper · explained in 2 episodes
• Structural Integrity — 1× in this paper · explained in 3 episodes
• World Model — 1× in this paper · explained in 7 episodes

Sources

• Cosmos 3: Omnimodal World Models for Physical AI
• eDiff-I: Text-to-Image Diffusion Models with an Ensemble of Expert Denoisers
• SRDiffusion: Accelerate Video Diffusion Inference via Sketching-Rendering Cooperation
• Photorealistic Video Generation with Diffusion Models
• Classifier-Free Diffusion Guidance
• SDXS: Real-Time One-Step Latent Diffusion Models with Image Conditions
• Wan: Open and Advanced Large-Scale Video Generative Models
• CogVideoX: Text-to-Video Diffusion Models with An Expert Transformer
• TurboDiffusion: Accelerating Video Diffusion Models by 100-200 Times

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