QClusformer: A Quantum Transformer-based Framework for Unsupervised Visual Clustering

Understand

Unsupervised vision clustering, a cornerstone in computer vision, has been studied for decades, yielding significant outcomes across numerous vision tasks.

• However, these algorithms involve substantial computational demands when confronted with vast amounts of unlabeled data.
• Conversely, quantum computing holds promise in expediting unsupervised algorithms when handling large-scale databases.
• In this study, we introduce QClusformer, a pioneering Transformer-based framework leveraging quantum machines to tackle unsupervised vision clustering challenges.