Papers › Optimal Transport Aggregation for Visual Place Recognition
Optimal Transport Aggregation for Visual Place Recognition
Sergio Izquierdo, Javier Civera
The task of Visual Place Recognition (VPR) aims to match a query image against references from an extensive database of images from different places, relying solely on visual cues. State-of-the-art pipelines focus on the aggregation of features extracted from a deep backbone, in order to form a global descriptor for each image. In this context, we introduce SALAD (Sinkhorn Algorithm for Locally Aggregated Descriptors), which reformulates NetVLAD's soft-assignment of local features to clusters as an optimal transport problem. In SALAD, we consider both feature-to-cluster and cluster-to-feature relations and we also introduce a 'dustbin' cluster, designed to selectively discard features deemed non-informative, enhancing the overall descriptor quality. Additionally, we leverage and fine-tune DINOv2 as a backbone, which provides enhanced description power for the local features, and dramatically reduces the required training time. As a result, our single-stage method not only surpasses single-stage baselines in public VPR datasets, but also surpasses two-stage methods that add a re-ranking with significantly higher cost. Code and models are available at https://github.com/serizba/salad.
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Code
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Code Syntology ran Syntology
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Tasks
Results from the paper archive 2025-07-28
| Task | Dataset | Model | Metric | Value | Rank at snapshot | Leaderboard | Report |
|---|---|---|---|---|---|---|---|
| Visual Place Recognition | Mapillary test | DINOv2 SALAD | Recall@1 | 75 | #8 of 12 | Archive leaderboard | report |
| Visual Place Recognition | Mapillary test | DINOv2 SALAD | Recall@10 | 91.3 | #8 of 12 | Archive leaderboard | report |
| Visual Place Recognition | Mapillary test | DINOv2 SALAD | Recall@5 | 88.8 | #8 of 12 | Archive leaderboard | report |
| Visual Place Recognition | Mapillary val | DINOv2 SALAD | Recall@1 | 92.2 | #8 of 18 | Archive leaderboard | report |
| Visual Place Recognition | Mapillary val | DINOv2 SALAD | Recall@10 | 97 | #8 of 18 | Archive leaderboard | report |
| Visual Place Recognition | Mapillary val | DINOv2 SALAD | Recall@5 | 96.4 | #8 of 18 | Archive leaderboard | report |
| Visual Place Recognition | Nordland | DINOv2 SALAD (1-frame thr.) | Recall@1 | 85.2 | #7 of 13 | Archive leaderboard | report |
| Visual Place Recognition | Nordland | DINOv2 SALAD (1-frame thr.) | Recall@5 | 98.5 | #7 of 13 | Archive leaderboard | report |
| Visual Place Recognition | Pittsburgh-250k-test | DINOv2 SALAD | Recall@1 | 95.1 | #6 of 13 | Archive leaderboard | report |
| Visual Place Recognition | Pittsburgh-250k-test | DINOv2 SALAD | Recall@10 | 99.1 | #6 of 13 | Archive leaderboard | report |
| Visual Place Recognition | Pittsburgh-250k-test | DINOv2 SALAD | Recall@5 | 98.5 | #6 of 13 | Archive leaderboard | report |
| Visual Place Recognition | SPED | DINOv2 SALAD | Recall@1 | 92.1 | #3 of 7 | Archive leaderboard | report |
| Visual Place Recognition | SPED | DINOv2 SALAD | Recall@10 | 96.5 | #3 of 7 | Archive leaderboard | report |
| Visual Place Recognition | SPED | DINOv2 SALAD | Recall@5 | 96.2 | #3 of 7 | Archive leaderboard | report |
Ranks are positions in the archive's leaderboards as they stood at the 2025-07-28 snapshot. Results published since then are not among these rows, so a rank here is not a current standing.
Methods
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