Bibliography (12):

1. ImageNet Large Scale Visual Recognition Challenge

2. Designing Network Design Spaces

3. SwAV: Unsupervised Learning of Visual Features by Contrasting Cluster Assignments

4. SimCLRv2: Big Self-Supervised Models are Strong Semi-Supervised Learners

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

6. Momentum Contrast for Unsupervised Visual Representation Learning

7. A Simple Framework for Contrastive Learning of Visual Representations

8. Bootstrap your own latent (BYOL): A new approach to self-supervised Learning

9. https://github.com/facebookresearch/vissl

10. Efficient Visual Pretraining with Contrastive Detection

11. DINO: Emerging Properties in Self-Supervised Vision Transformers

12. Wikipedia Bibliography:

    1. Weak supervision § Semi-supervised learning