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Visual recognition is recently learned via either supervised learning on human-annotated image-label data or language-image contrastive learning with webly-crawled image-text pairs.
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nocaps: novel object captioning at scale
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Learning transferable visual models from natural language supervision
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Cvt: Introducing convolutions to vision transformers
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Florence: A new foundation model for computer vision
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Multi-scale vision longformer: A new vision transformer for high-resolution image encoding
Pengchuan Zhang, Xiyang Dai, Jianwei Yang, Bin Xiao, Lu Yuan, Lei Zhang, and Jianfeng Gao · 2021
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Vinvl: Revisiting visual representations in vision-language models
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