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Faster or Stronger: Towards Flexible Visual Place Recognition via Weighted Aggregation and Token Pruning

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Faster or Stronger: Towards Flexible Visual Place Recognition via Weighted Aggregation and Token Pruning
TL;DR · WeSearch summary

The paper presents advancements in Visual Place Recognition (VPR) through a new method called Weighted Aggregated Descriptor (WeiAD). This method improves the aggregation of patch tokens by assigning weights to clusters, enhancing the accuracy of global representations. Additionally, the authors introduce WeiToP, a token pruning framework that optimizes feature extraction costs while maintaining performance.

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Record

Original publisherarXiv cs.AI
Canonical URLhttps://arxiv.org/abs/2605.20551
Publication timeFri, 22 May 2026 00:00:00 -0400
Retrieval time2026-05-22T04:02:00.009Z
Last seen2026-05-22T04:02:00.009Z
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Basis: Derived from the published RSS/Atom feed. Contact: [email protected]. Reviewed: 2026-07-24.

Opening excerpt (first ~120 words) tap to expand

Computer Science > Computer Vision and Pattern Recognition arXiv:2605.20551 (cs) [Submitted on 19 May 2026] Title:Faster or Stronger: Towards Flexible Visual Place Recognition via Weighted Aggregation and Token Pruning Authors:Zichao Zeng, June Moh Goo, Junwei Zheng, Weijia Fan, Jiaming Zhang, Rainer Stiefelhagen, Jan Boehm View a PDF of the paper titled Faster or Stronger: Towards Flexible Visual Place Recognition via Weighted Aggregation and Token Pruning, by Zichao Zeng and 6 other authors View PDF HTML (experimental) Abstract:Visual Place Recognition (VPR) aims to match a query image to reference images of the same place in a large-scale database.

Excerpt limited to ~120 words for fair-use compliance. The full article is at arXiv cs.AI.

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