A new large dataset for illumination estimation. This dataset, called INTEL-TAU, contains 7022 images in total, which makes it the largest available high-resolution dataset for illumination estimation research.
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VegFru is a domain-specific dataset for fine-grained visual categorization. VegFru categorizes vegetables and fruits according to their eating characteristics, and each image contains at least one edible part of vegetables or fruits with the same cooking usage. Particularly, all the images are labelled hierarchically. The current version covers vegetables and fruits of 25 upper-level categories and 292 subordinate classes. And it contains more than 160,000 images in total and at least 200 images for each subordinate class.
A dataset of over 65,000 pairs of incorrectly white-balanced images and their corresponding correctly white-balanced images.
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Cube++ is a novel dataset for the color constancy problem that continues on the Cube+ dataset. It includes 4890 images of different scenes under various conditions. For calculating the ground truth illumination, a calibration object with known surface colors was placed in every scene.
5 PAPERS • 1 BENCHMARK
Large Scale Multi-Illuminant (LSMI) Dataset for Developing White Balance Algorithm under Mixed Illumination (ICCV 2021) <!-- ABOUT THE PROJECT -->
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