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1. CLIP: Connecting Text and Images: We’re introducing a neural network called CLIP which efficiently learns visual concepts from natural language supervision. CLIP can be applied to any visual classification benchmark by simply providing the names of the visual categories to be recognized, similar to the ‘zero-shot’ capabilities of GPT-2 and GPT-3

2. https://github.com/klauscc/VindLU

3. Vision Transformer: An Image is Worth 16×16 Words: Transformers for Image Recognition at Scale

4. MSR-VTT: A Large Video Description Dataset for Bridging Video and Language

5. Dense-Captioning Events in Videos

6. Attention Is All You Need

7. ConvNeXt: A ConvNet for the 2020s