Memory-V2V is a framework that augments video-to-video diffusion models with explicit memory to ensure cross-consistency across multiple iterative editing turns. It uses retrieval and dynamic tokenization of previously edited videos, alongside a learnable token compressor for efficiency.
Memory-V2V is a new system that helps AI video editors keep videos consistent when users make many changes over time. It does this by giving the AI a memory of past edits and efficiently using that information to guide new changes, making the process faster and more coherent.
Memory-V2V, multi-turn video editing framework, memory-augmented video diffusion
Was this definition helpful?