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Dataset assetOpen Source CommunityImage ProcessingIllumination Variation
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.
Source
github
Created
May 31, 2022
Updated
May 12, 2024
Signals
149 views
Availability
Linked source ready
Overview
Dataset description and usage context
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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