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FLAVA: A Foundational Language And Vision Alignment Model

2021-12-08CVPR 2022Code Available1· sign in to hype

Amanpreet Singh, Ronghang Hu, Vedanuj Goswami, Guillaume Couairon, Wojciech Galuba, Marcus Rohrbach, Douwe Kiela

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Abstract

State-of-the-art vision and vision-and-language models rely on large-scale visio-linguistic pretraining for obtaining good performance on a variety of downstream tasks. Generally, such models are often either cross-modal (contrastive) or multi-modal (with earlier fusion) but not both; and they often only target specific modalities or tasks. A promising direction would be to use a single holistic universal model, as a "foundation", that targets all modalities at once -- a true vision and language foundation model should be good at vision tasks, language tasks, and cross- and multi-modal vision and language tasks. We introduce FLAVA as such a model and demonstrate impressive performance on a wide range of 35 tasks spanning these target modalities.

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Benchmark Results

DatasetModelMetricClaimedVerifiedStatus
COCO (Common Objects in Context)FLAVA (zero-shot)recall@138.38Unverified
COCO (Common Objects in Context)CLIP (zero-shot)recall@133.29Unverified

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