CVPR 2022poster796 citations

FLAVA: A Foundational Language and Vision Alignment Model

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

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.

BibTeX
@inproceedings{cvpr2022_flavaafoundation,
  title = {FLAVA: A Foundational Language and Vision Alignment Model},
  author = {Amanpreet Singh and Ronghang Hu and Vedanuj Goswami and Guillaume Couairon and Wojciech Galuba and Marcus Rohrbach and Douwe Kiela},
  booktitle = {CVPR 2022},
  year = {2022}
}
FLAVA: A Foundational Language and Vision Alignment Model · CVPR 2022