HYouTube: Video Harmonization Dataset
This provides a resource for researchers in video editing and computer vision, though it is incremental as it focuses on dataset creation rather than new methods.
The paper tackles the lack of a public dataset for video harmonization, which adjusts foregrounds in composite videos to match backgrounds, by constructing the HYouTube dataset with synthetic and real composite videos.
Video composition aims to generate a composite video by combining the foreground of one video with the background of another video, but the inserted foreground may be incompatible with the background in terms of color and illumination. Video harmonization aims to adjust the foreground of a composite video to make it compatible with the background. So far, video harmonization has only received limited attention and there is no public dataset for video harmonization. In this work, we construct a new video harmonization dataset HYouTube by adjusting the foreground of real videos to create synthetic composite videos. Considering the domain gap between real composite videos and synthetic composite videos, we additionally create 100 real composite videos via copy-and-paste. Datasets are available at https://github.com/bcmi/Video-Harmonization-Dataset-HYouTube.