SNLI-VE
Introduced by Xie et al. in Visual Entailment: A Novel Task for Fine-Grained Image Understanding
Visual Entailment (VE) consists of image-sentence pairs whereby a premise is defined by an image, rather than a natural language sentence as in traditional Textual Entailment tasks. The goal of a trained VE model is to predict whether the image semantically entails the text. SNLI-VE is a dataset for VE which is based on the Stanford Natural Language Inference corpus and Flickr30k dataset.
Source: https://github.com/necla-ml/SNLI-VEBenchmarks
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SNLI-VE val
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OFA
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SNLI-VE test
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OFA
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Papers
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