@inproceedings{
havaldar2023visual,
title={Visual Topics via Visual Vocabularies},
author={Shreya Havaldar and Weiqiu You and Lyle Ungar and Eric Wong},
booktitle={XAI in Action: Past, Present, and Future Applications},
year={2023},
url={https://openreview.net/forum?id=h6OT5pzrGc}
}
Researchers have long used topic modeling to automatically characterize and summarize text documents without supervision. Can we extract similar structures from collections of images? To do this, we propose visual vocabularies, a method to analyze image datasets by decomposing images into segments, and grouping similar segments into visual "words". These vocabularies of visual "words" enable us to extract visual topics that capture hidden themes distinct from what is captured by classic unsupervised approaches. We evaluate our visual topics using standard topic modeling metrics and confirm the coherency of our visual topics via a human study.
Visual Topics via Visual Vocabularies
Shreya Havaldar Weiqiu You Lyle Ungar Eric Wong