Filtered to video editing · clear filter
This paper introduces VideoCoCo, a system that uses executable Blender code to generate physically consistent videos from text prompts, and shows promising results in improving video generation quality. Practitioners might care about this research if they want to generate realistic videos that are also physically plausible.
This paper creates a new AI model that can edit and generate videos without needing masks, and can also learn to mimic image editing capabilities. Practitioners might care about this because it could lead to more diverse and realistic video editing data, and enable AI models to understand and generate human-like video editing instructions.
This paper develops a new method for editing videos with explicit layered representations, which allows for more realistic compositing, object reuse, and manipulation. Practitioners working on video editing and compositing might care about this research as it could lead to improved video editing tools.