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arXiv · 2409.11923

Agglomerative Token Clustering

Joakim Bruslund Haurum·Sergio Escalera·Graham W. Taylor·Thomas B. Moeslund
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Abstract

We present Agglomerative Token Clustering (ATC), a novel token merging method that consistently outperforms previous token merging and pruning methods across image classification, image synthesis, and object detection & segmentation tasks. ATC merges clusters through bottom-up hierarchical clustering, without the introduction of extra learnable parameters. We find that ATC achieves state-of-the-art performance across all tasks, and can even perform on par with prior state-of-the-art when applied off-the-shelf, i.e. without fine-tuning. ATC is particularly effective when applied with low keep rates, where only a small fraction of tokens are kept and retaining task performance is especially difficult.

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Joakim Bruslund Haurum, Sergio Escalera, Graham W. Taylor, Thomas B. Moeslund. 2024-09-18. Agglomerative Token Clustering. https://arxiv.org/abs/2409.11923

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