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Updated: Jun 9, 2025
10:41
Using Electroencephalography Measurements and High-quality Video Recording for Analyzing Visual Perception of Media Content
Published on: May 26, 2018
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Cut-and-Paste: Subject-driven video editing with attention control.
Zhichao Zuo1, Zhao Zhang2, Yan Luo1
1School of Computer Science and Information Engineering, Hefei University of Technology, Hefei, China.
Summary
This study introduces Cut-and-Paste, a novel framework for semantic video editing. It uses text prompts and reference images for precise object editing while preserving backgrounds and spatio-temporal consistency.
Area of Science:
- Computer Vision
- Artificial Intelligence
- Multimedia Processing
Background:
- Text-driven video editing offers diverse generation but lacks fine-grained control over object details and edited regions.
- Cumbersome text descriptions are often required for precise semantic control in video editing tasks.
Purpose of the Study:
- To develop a subject-driven video editing framework for precise control over edited regions and background preservation.
- To enable fine-grained semantic generation in videos using supplementary reference images alongside text prompts.
- To simplify the video editing process by avoiding lengthy text descriptions for detailed object appearances.
Main Methods:
- Introduced a novel framework named Cut-and-Paste for real-world semantic video editing.
- Integrated a reference image as supplementary input to text-driven video editing for subject-driven control.
- Extended cross-attention control from image editing to video editing by fusing attention maps of adjacent frames.
- Achieved a balance between background preservation and spatio-temporal consistency in edited videos.
Main Results:
- The Cut-and-Paste framework enables precise "cutting" of source objects and "pasting" of target objects guided by reference images.
- Demonstrated favorable performance over prior art in video editing tasks requiring text prompts and reference images.
- Quantitative and subjective evaluations confirmed the effectiveness of the proposed method.
Conclusions:
- The Cut-and-Paste framework significantly enhances control and precision in semantic video editing.
- Using reference images alongside text prompts simplifies detailed object editing and improves background preservation.
- The method offers a practical and effective solution for subject-driven video editing with improved spatio-temporal consistency.
Keywords:
Attention control with adjacent framesFine-grained semantic editsSubject drivenVideo editingMore Related Videos
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