README.md

metadata

license: cc-by-nc-4.0
task_categories:
  - image-to-image
tags:
  - color-transfer
  - indoor-scene

Intrinsic Decomposition Dataset

The Interior Decomposition Dataset (IDD) is a dataset designed to analyze how intrinsic scene properties influence the perceived quality of color transfer methods. It consists of photorealistic, synthetically rendered indoor scenes with systematically controlled variations in color, illumination, geometry, object arrangement, and viewpoint. In addition to the rendered images, the dataset provides detailed ground-truth information such as semantic segmentation, depth, and physically-based rendering passes.

Dataset Viewer

Details

• The dataset consists of 4 photorealistic indoor scenes with systematically controlled variations.
• Each scene is provided in 4 different color configurations, 8 distinct illumination settings, 4 different object arrangements, and 6 camera viewpoints.
• In total, the dataset contains 3,072 unique scene instances.
• All images are stored at a resolution of 1024 × 1024 pixels in 32-bit floating-point EXR format using a linear RGB color space.
• Each scene instance includes a semantic map with 26 channels representing object classes using soft assignments.
• Depth maps are provided with values ranging from 0 to 15 meters, normalized to the interval [0, 1].
• Normal maps are available in both world-space and view-space representations.
• Pixel size maps encode the estimated real-world surface area covered by each pixel based on depth and viewing angle.
• A beauty pass decomposition is included, consisting of 14 rendering channels such as diffuse and reflection components.
• The rendered images are released under a Creative Commons CC BY-NC 4.0 license, while the original 3D models are not included.

Figure 1: Scene variations

Figure 2: Extract from the IDD: base scene, with variations in color statistics (top left to right), illumination, object arrangement, and view (bottom left to right).

Figure 3: Illustration of scene cues for color transfer: semantic map, size map, diffuse pass (left to right).

Citation

If you utilize this dataset in your research, kindly provide a citation:

@inproceedings{potechius2026,
    author={Potechius, H. and Sikora, T. and Knorr, S.},
    booktitle={IEEE International Conference on Image Processing (ICIP)}, 
    title={{The Impact of Intrinsic Scene Cues on Perceived Color Transfer Quality}}, 
    year={2026},
    location = {Tampere, Finland}
}