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We present RECLIP (Resource-efficient CLIP), a simple method that minimizes computational resource footprint for CLIP (Contrastive Language Image Pretraining).
ImageNet: A Large-Scale Hierarchical Image Database
J. Deng, W. Dong, R. Socher, L.-J. Li, K. Li, and L. Fei-Fei · 2009
Earlier work this paper cites.
Learning models for object recognition from natural language descriptions
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Learning everything about anything: Webly-supervised visual concept learning
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Webly supervised learning of convolutional networks
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Bryan A Plummer, Liwei Wang, Chris M Cervantes, Juan C Caicedo, Julia Hockenmaier, and Svetlana Lazebnik · 2015
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Masked autoencoders are scalable vision learners
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Self supervision does not help natural language supervision at scale, 2023
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