Streaming Video Editing with Easy Adaptation

arXiv:2609.24788 · cs.CV · Submitted 2026-09-21 · Read on arXiv

cs.CV

Submitted: 2026-09-21

Updated: 2026-09-21

Terminology

• Consistency — 18× in this paper · explained in 3 episodes
• Diffusion Model — 17× in this paper · explained in 8 episodes
• Diffusion Models — 14× in this paper · explained in 6 episodes
• Distillation — 12× in this paper · explained in 2 episodes
• Orthogonal Decoupled Training — 9× in this paper
• Adam — 5× in this paper · explained in 2 episodes
• Adaptation — 5× in this paper · explained in 1 episode
• Alignment — 5× in this paper · explained in 1 episode
• Decoupling — 5× in this paper · explained in 2 episodes
• Zero-Shot Transfer — 4× in this paper · explained in 4 episodes
• Accuracy — 3× in this paper · explained in 1 episode
• Ablation — 2× in this paper · explained in 1 episode
• Additivity — 2× in this paper · explained in 1 episode
• Calibration — 2× in this paper · explained in 7 episodes
• Core — 2× in this paper · explained in 2 episodes
• Distribution Matching — 2× in this paper · explained in 2 episodes
• Fine-Tuning — 2× in this paper · explained in 5 episodes
• Generative Model — 2× in this paper · explained in 2 episodes
• Generative Models — 2× in this paper · explained in 2 episodes
• LoRA Adapters — 2× in this paper · explained in 3 episodes
• Model Merging — 2× in this paper · explained in 2 episodes
• Regularization — 2× in this paper · explained in 3 episodes
• Transformer — 2× in this paper · explained in 2 episodes
• AdamW Optimizer — 1× in this paper · explained in 1 episode
• Benchmark — 1× in this paper · explained in 2 episodes
• Cosine Similarity — 1× in this paper · explained in 3 episodes
• Fidelity — 1× in this paper · explained in 2 episodes
• Generalization — 1× in this paper · explained in 13 episodes
• KV cache — 1× in this paper · explained in 3 episodes
• Latent Diffusion Model — 1× in this paper · explained in 2 episodes
• Latent Diffusion Models — 1× in this paper · explained in 2 episodes
• Representation Learning — 1× in this paper · explained in 2 episodes
• Temporal consistency — 1× in this paper · explained in 2 episodes
• Transferability — 1× in this paper · explained in 4 episodes
• Verification — 1× in this paper · explained in 2 episodes
• Video Condition Unit — 1× in this paper

Sources

• Scaling Instruction-Based Video Editing with a High-Quality Synthetic Dataset
• Stable Video Diffusion: Scaling Latent Video Diffusion Models to Large Datasets
• Consistent Video-to-Video Transfer Using Synthetic Dataset
• Whoever Started the Interference Should End It: Guiding Data-Free Model Merging via Task Vectors
• StreamDiffusionV2: A Streaming System for Dynamic and Interactive Video Generation
• Adapting VACE for Real-Time Autoregressive Video Diffusion
• LoRA: Low-Rank Adaptation of Large Language Models
• Self Forcing: Bridging the Train-Test Gap in Autoregressive Video Diffusion
• GPT-4o System Card
• HunyuanVideo: A Systematic Framework For Large Video Generative Models
• Sora: A Review on Background, Technology, Limitations, and Opportunities of Large Vision Models
• Decoupled Weight Decay Regularization
• Latent Consistency Models: Synthesizing High-Resolution Images with Few-Step Inference
• SDEdit: Guided Image Synthesis and Editing with Stochastic Differential Equations
• Progressive Distillation for Fast Sampling of Diffusion Models
• Make-A-Video: Text-to-Video Generation without Text-Video Data
• Denoising Diffusion Implicit Models
• Phenaki: Variable Length Video Generation From Open Domain Textual Description
• Wan: Open and Advanced Large-Scale Video Generative Models
• LiveEdit: Towards Real-Time Diffusion-Based Streaming Video Editing

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