VirTex: Learning Visual Representations from Textual Annotations
We train CNN+Transformer from scratch from COCO, transfer the CNN to 6 downstream vision tasks, and exceed ImageNet features despite using 10x fewer ...
convolutional-neural-networks transformers coco visual-representations image-captioning object-detection transfer-learning pytorch pretraining natural-language-processing computer-vision article code paper arxiv:2006.06666 virtex tutorial research
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VirTex is a pretraining approach which uses semantically dense captions to learn visual representations. We train CNN + Transformers from scratch on COCO Captions, and transfer the CNN to downstream vision tasks including image classification, object detection, and instance segmentation. VirTex matches or outperforms models which use ImageNet for pretraining -- both supervised or unsupervised -- despite using up to 10x fewer images.

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