Papers › BargainNet: Background-Guided Domain Translation for Image Harmonization

BargainNet: Background-Guided Domain Translation for Image Harmonization

19 Sep 2020arXiv:2009.09169archive 2025-07-28

Wenyan Cong, Li Niu, Jianfu Zhang, Jing Liang, Liqing Zhang

Image composition is a fundamental operation in image editing field. However, unharmonious foreground and background downgrade the quality of composite image. Image harmonization, which adjusts the foreground to improve the consistency, is an essential yet challenging task. Previous deep learning based methods mainly focus on directly learning the mapping from composite image to real image, while ignoring the crucial guidance role that background plays. In this work, with the assumption that the foreground needs to be translated to the same domain as background, we formulate image harmonization task as background-guided domain translation. Therefore, we propose an image harmonization network with a novel domain code extractor and well-tailored triplet losses, which could capture the background domain information to guide the foreground harmonization. Extensive experiments on the existing image harmonization benchmark demonstrate the effectiveness of our proposed method. Code is available at https://github.com/bcmi/BargainNet.

PaperPDFCode

In Syntology Open this paper in Syntology's Atlas, the map of the papers in Syntology's graph and their citations.

Code

bcmi/BargainNet-Image-Harmonization officialmentioned on GitHubpytorch report

Repository list and official/mentioned flags are the archive's, frozen 2025-07-28. Reachability, where shown, is from one Syntology probe window (2026-09-16 to 2026-09-18); repositories not probed show nothing. GitHub stars are not tracked.

Code Syntology ran Syntology

Not run by Syntology. Nothing on this page verifies that the listed code works.

Tasks

Image HarmonizationTranslation

1 archive task tag without a task page not shown.

Results from the paper archive 2025-07-28

TaskDatasetModelMetricValueRank at snapshotLeaderboardReport
Image Harmonization iHarmony4 BargainNet MSE 37.82 #13 of 16 Archive leaderboard report
Image Harmonization iHarmony4 BargainNet PSNR 35.88 #13 of 16 Archive leaderboard report
Image Harmonization iHarmony4 BargainNet fMSE 405.23 #13 of 16 Archive leaderboard report

Ranks are positions in the archive's leaderboards as they stood at the 2025-07-28 snapshot. Results published since then are not among these rows, so a rank here is not a current standing.

Report a problem or propose a change · a person checks every report against the paper or source before anything changes; decisions are listed on /corrections