A new multitask action quality assessment (AQA) dataset, the largest to date, comprising of more than 1600 diving samples; contains detailed annotations for fine-grained action recognition, commentary generation, and estimating the AQA score. Videos from multiple angles provided wherever available.
24 PAPERS • 2 BENCHMARKS
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.
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FoodX-251 is a dataset of 251 fine-grained classes with 118k training, 12k validation and 28k test images. Human verified labels are made available for the training and test images. The classes are fine-grained and visually similar, for example, different types of cakes, sandwiches, puddings, soups, and pastas.
8 PAPERS • 1 BENCHMARK
The L-Bird (Large-Bird) dataset contains nearly 4.8 million images which are obtained by searching images of a total of 10,982 bird species from the Internet.
2 PAPERS • NO BENCHMARKS YET
The FeatherV1 dataset is a dataset for fine-grained visual classification. It contains 28,272 images of feathers categorized by 595 bird species.
1 PAPER • NO BENCHMARKS YET