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ccHarmony
The ccHarmony dataset is a color‑checker‑based image harmonization dataset designed to better reflect natural illumination variations while maintaining a distribution similar to the Hday2night dataset, but at a lower collection cost. It comprises 350 real images and 426 segmented foregrounds; each foreground is paired with 10 synthetic composite images, resulting in a total of 4,260 synthetic‑real image pairs.
Updated 5/12/2024
github
Description
Dataset Overview
Dataset Name
ccHarmony
Dataset Characteristics
- Image harmonization dataset based on a color checker (cc).
- By transferring foregrounds from real images to a standard illumination condition and then to another illumination condition, synthetic composite images are generated.
- Contains 4,260 synthetic‑real image pairs, divided into 3,080 training pairs and 1,180 testing pairs.
Dataset Content
- 350 real images.
- 426 segmented foregrounds, each associated with 10 synthetic composite images.
Dataset Download
Experimental Results
- Multiple image harmonization methods were evaluated, including DoveNet, RainNet, IIH, etc.
- Results show that our proposed GiftNet achieves the best performance on MSE, fMSE, PSNR, and fSSIM metrics.
Dataset Examples
- Several real images and their corresponding synthetic composites are displayed.
Dataset Applications
- Suitable for research and testing of image harmonization methods.
- Supports dataset augmentation via SycoNet to generate high‑quality composite images.
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Topics
Image Processing
Illumination Variation
Source
Organization: github
Created: 5/31/2022
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