Is this kind of happening with the CLIP classifier [1] to rank the generated images? > Similar to the rejection sampling used in VQVAE-2, we use CLIP to rerank

Is this kind of happening with the CLIP classifier [1] to rank the generated images? > Similar to the rejection sampling used in VQVAE-2, we use CLIP to rerank the top 32 of 512 samples for each caption in all of the interactive visuals. This procedure can also be seen as a kind of language-guided search16, and can have a dramatic impact on sample quality. > CLIP pre-trains an image encoder and a text encoder to predict which images were paired with which texts in our dataset. We then use this behavior to turn CLIP into a zero-shot classifier. We convert all of a dataset’s classes into captions such as “a photo of a dog” and predict the class of the caption CLIP estimates best pairs with a given image. [1] https://openai.com/blog/clip/ https://openai.com/blog/clip/