ImageNet Classification with Deep Convolutional Neural Networks
A deep convolutional network demonstrated how data, GPU computation and learned representations could transform visual recognition.
THE RESEARCH ATLAS
Learning Transferable Visual Models From Natural Language Supervision
Contrastive training aligns images with natural-language descriptions, enabling transfer to new visual categories.
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Why read this
An essential bridge between vision, language and open-vocabulary perception.
Citation
@misc{radford2021learning,
title = {Learning Transferable Visual Models From Natural Language Supervision},
author = {Alec Radford and Jong Wook Kim and Chris Hallacy and Aditya Ramesh and Gabriel Goh and Sandhini Agarwal and Girish Sastry and Amanda Askell and Pamela Mishkin and Jack Clark and Gretchen Krueger and Ilya Sutskever},
year = {2021},
eprint = {2103.00020},
archivePrefix = {arXiv},
primaryClass = {cs.CV},
url = {https://arxiv.org/abs/2103.00020}
}Rights remain with the original authors. Refer to the original source for citations and licensing.
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