Bibliography (7):

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. ALIGN: Scaling Up Visual and Vision-Language Representation Learning With Noisy Text Supervision

3. Unified Contrastive Learning in Image-Text-Label Space

4. ImageNet Large Scale Visual Recognition Challenge

5. Microsoft COCO: Common Objects in Context

6. A Short Note about Kinetics-600

7. Wikipedia Bibliography:

   1. Object detection