OpenAI's CLIP Explained and Implementation | Contrastive Learning | Self-Supervised Learning

CLIP (Contrastive Language-Image Pre-Training) is a neural network trained on a variety of (image, text) pairs. It can be instructed in natural language to predict the most relevant text snippet, given an image, without directly optimizing for the task, similarly to the zero-shot capabilities of GPT-2 and 3. We found CLIP matches the performance of the original ResNet50 on ImageNet “zero-shot” without using any of the original 1.28M labeled examples, overcoming several major challenges in computer vision.

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[muhammadumer-qktx]

Really helpful for me to understand the CLIP concept. Thank you

[anuradhabalasubramanian]

Excellent presentation ! Very simplified

[lakatosgabor]

Hy! Can you give me the loss function formula?

[dunghuy]

The formula of the targets is incorrect. It should be torch.arange(n). In fact, the goal is to make the similarity matrix become an indentity matrix.

[robboswell]

Nice video about training CLIP. I tried to connect to your Kaggle notebook and it is saying that it is no longer there (404 error). Is there a different link we could access your notebook from the video on?