Papers for

advertising video editors

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AI tools speed up small detailed edits in film making

Micro-Edits: Computational Support for Fine-Scale Edits in Film

Abstract: In film editing, every frame matters. While macro, content-level edits shape the high-level narrative of a film, small local edits often control timing and direct visual attention. For example, editors can adjust the precise timing of clips to control the length of a meaningful silence, or cut to shots that highlight a specific character's reactions to important moments. These small, detailed edits are slow and tedious to make in standard editing tools because users have to map high-level narrative goals to low-level frame-by-frame adjustments. At the same time, these fine-scale adjustments, which we call micro-edits, can be nuanced and expressive, with different choices serving different creative goals. In this work, we start by conducting a formative study with professional editors to understand the structure of micro-edits and how they are used. We then derive a mathematical formalization for this structure to develop tools that leverage AI and optimization to make exploring micro-edits simpler and more efficient for users. Finally, we validate our tools in multiple user studies and a wide range of video examples.

Thu 29 OctHuman-Computer InteractionComputer Vision and Pattern Recognition
The gist
Editing movies is tricky because every little change in timing or shot can change how a story feels. The authors studied professional editors to learn how these tiny changes, called micro-edits, are made and why they matter. They created a math-based system that uses AI to help editors try out these small adjustments more easily and quickly. They tested their tools with real users and different videos to make sure they work well.
Open → 2610.40653v1