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ALIGN-BENCH is developed for measuring cross-modal alignment of vision-language models quantitatively.
The code can be found at https://github.com/IIGROUP/SCL.
The core idea is to utilize the cross-attention maps of the last layer in fusion encoder, and compare them with annotated regions corresponding to some words.
ALIGN-BENCH can calculate global-local and local-local alignment scores from two angles, bounding box and pixel mask.
There are 1,500 images and 1,500 annotation files in the dataset zip file. The annotatino file contains a caption and some words' regions (bounding box and pixel mask) on the image.
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