Searching for Images using Semantics
Suppose you are given a huge set of images. But you do not know what is in them. How do you start?
We have developed a method to cluster images and give each cluster a meaningful name. For each image, we assign an initial label from a large set of candidate words. We do this by a language-vision model: CLIP from OpenAI.
Next, we look for the word that best describes all images in the cluster. Possibly that could be a container name. We look into the coarse-to-fine hierarchy of all labels in the cluster, taken from Wordnet. In this way, we can assign Bird to a cluster containing images of Swans, Owls and Parrots.