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Masking and Demasking Agents

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Related Experiment Video

Updated: May 15, 2026

Combining Eye-tracking Data with an Analysis of Video Content from Free-viewing a Video of a Walk in an Urban Park Environment

Combining Eye-tracking Data with an Analysis of Video Content from Free-viewing a Video of a Walk in an Urban Park Environment

Published on: May 7, 2019

MultiPaint: A Unified Framework for Multi-Task, Multi-Object, and Multi-Condition Video Inpainting.

Shiyuan Yang, Zheng Gu, Liang Hou

IEEE Transactions on Visualization and Computer Graphics

|May 13, 2026

Summary

This summary is machine-generated.

MultiPaint unifies video inpainting for multiple objects and tasks, enabling both insertion and completion. This advanced framework improves multi-object interaction and appearance customization for better video editing.

Related Experiment Videos

Last Updated: May 15, 2026

Combining Eye-tracking Data with an Analysis of Video Content from Free-viewing a Video of a Walk in an Urban Park Environment

Combining Eye-tracking Data with an Analysis of Video Content from Free-viewing a Video of a Walk in an Urban Park Environment

Published on: May 7, 2019

Area of Science:

Computer Vision
Artificial Intelligence
Machine Learning

Background:

Existing video inpainting methods struggle with unified support for insertion and completion tasks.
Current approaches are limited to single-object inpainting, hindering multi-object scenarios with interactions.

Purpose of the Study:

To introduce MultiPaint, a unified framework for multi-task, multi-object, and multi-condition video inpainting.
To enhance controllability and performance in complex video editing scenarios.

Main Methods:

Utilized dual-branch adapters to unify insertion and completion tasks within a single model.
Implemented a test-time scheduled feature composition strategy for multi-object inpainting with interaction preservation.
Introduced a multi-condition inpainting scheme (text, image, keyframe-guided) via dynamic frame masking.

Main Results:

Achieved state-of-the-art performance in object insertion and scene completion tasks.
Demonstrated superior handling of multi-object scenarios and interactions.
Showcased versatility in downstream applications like grounded video generation and object editing.

Conclusions:

MultiPaint offers a unified and versatile solution for advanced video inpainting.
The framework significantly improves upon existing methods for complex multi-object and multi-condition video editing.