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Datasets/Flickr30K-Noisy

Flickr30K-Noisy

Flickr-30K with 20% of Noisy Correspondence

ImagesIntroduced 2021-12-01

This dataset, based on Flickr30K, is introduced in Learning with Noisy Correspondence for Cross-modal Matching. Noisy correspondence is simulated by randomly shuffling the captions of training images for a specific percentage, denoted by noise ratio

Benchmarks

Cross-Modal Information Retrieval/R-SumCross-Modal Information Retrieval/Image-to-text R@1Cross-Modal Information Retrieval/Image-to-text R@5Cross-Modal Information Retrieval/Image-to-text R@10Cross-Modal Information Retrieval/Text-to-image R@1Cross-Modal Information Retrieval/Text-to-image R@5Cross-Modal Information Retrieval/Text-to-image R@10Cross-Modal Retrieval/R-SumCross-Modal Retrieval/Image-to-text R@1Cross-Modal Retrieval/Image-to-text R@5Cross-Modal Retrieval/Image-to-text R@10Cross-Modal Retrieval/Text-to-image R@1Cross-Modal Retrieval/Text-to-image R@5Cross-Modal Retrieval/Text-to-image R@10Image Retrieval with Multi-Modal Query/R-SumImage Retrieval with Multi-Modal Query/Image-to-text R@1Image Retrieval with Multi-Modal Query/Image-to-text R@5Image Retrieval with Multi-Modal Query/Image-to-text R@10Image Retrieval with Multi-Modal Query/Text-to-image R@1Image Retrieval with Multi-Modal Query/Text-to-image R@5Image Retrieval with Multi-Modal Query/Text-to-image R@10

Statistics

Papers
16
Benchmarks
21

Links

Tasks

Cross-Modal Information RetrievalCross-Modal RetrievalCross-modal retrieval with noisy correspondenceImage Retrieval with Multi-Modal Query