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About Learning Transferable Visual Models From Natural Language Supervision
1. The document presents a method for training visual models using natural language supervision from large datasets of image-text pairs collected from the internet, without requiring category labels. 2. The simple pre-training task of predicting which caption matches each image is shown to learn state-of-the-art image representations from scratch. 3. After pre-training, the model can transfer to over 30 computer vision tasks through zero-shot learning using natural language, matching a fully supervised ResNet-50 on ImageNet without using any ImageNet labels.
Detailed Information
| Author: | ['Tzu-Hsien Tsai'] |
|---|---|
| Publication Year: | 2021 |
| Pages: | 48 |
| Language: | English |
| Format: | |
| Price: | FREE |
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