Hindi Visual Genome is a multimodal dataset consisting of text and images suitable for English-to-Hindi multimodal machine translation task and multimodal research.

The short English segments (captions) were randomly selected from Visual Genome along with associated images. We automatically translated the captions to Hindi and manually corrected the translations, taking the associated images into account.

The training set contains 30K segments and it is accompanied with a development set (dtest, 1K segments) and evaluation set (etest, 1K segments) from the same distribution.

Additionally, we prepared a challenge test set of 1400 segments (chtest). This test set was created by searching for particularly ambiguous English words based on the embedding similarity and manually selecting those where the image helps to resolve the ambiguity. The Hindi translation of the English captions were manually corrected in the same way as the main data sets.

Dataset Sample

Sample items from the randomly selected segments (train/dtest/etest)

Image Image_ID X Y Width Height English Text Hindi Text
2323457 2323457 20 150 325 121 Many giraffes at a zoo एक चिड़ियाघर में कई जिराफ़
2335684 2335684 61 191 437 182 Fruit stand outside market बाजार के बाहर फल स्टैंड

Sample item from the challenge test set (chtest)

2372733 2372733 26 107 152 218 The tennis court is made up of sand and dirt य़ह टेनिस कोर्ट रेत और धूल से बना है

Sample ambiguous word: court (the key different meanings are court of justice vs. tennis court). As the image example illustrates, the word alone is ambiguous but already the English caption may contain sufficient information to disambiguate the word; the image is thus not always necessary for correct translation even in our challenge test set.

About Release

Hindi Visual Genome now goes through the final verification and it will be released in Spring 2019; free of charge for non-commercial and research purposes.