MMS-VPR: A Fine-Grained Multimodal Street-Level Visual Place Recognition Dataset and Evaluation Benchmark for Dense Pedestrian Environments

arXiv:2505.12254 · cs.CV, cs.AI, cs.LG · Submitted 2025-05-18 · Read on arXiv

cs.CV, cs.AI, cs.LG

Submitted: 2025-05-18

Updated: 2026-09-20

Comments: 27 pages, 19 figures

Code: https://github.com/yiasun/MMS-VPRlib

License: http://arxiv.org/licenses/nonexclusive-distrib/1.0/

Terminology

• Benchmark — 39× in this paper · explained in 2 episodes
• Visual Place Recognition — 34× in this paper
• Transformer — 29× in this paper · explained in 2 episodes
• Accuracy — 14× in this paper · explained in 1 episode
• Alignment — 9× in this paper · explained in 1 episode
• Aggregation — 7× in this paper · explained in 1 episode
• Robustness — 7× in this paper · explained in 5 episodes
• Benchmarking — 6× in this paper · explained in 3 episodes
• Conference on Computer Vision and Pattern Recognition — 4× in this paper
• CVF International Conference on Computer Vision — 3× in this paper
• International Conference on Robotics and Automation — 3× in this paper
• Multimodal Fusion — 3× in this paper · explained in 3 episodes
• Adaptation — 2× in this paper · explained in 1 episode
• Core — 2× in this paper · explained in 2 episodes
• Distillation — 2× in this paper · explained in 2 episodes
• Foundation Model — 2× in this paper · explained in 3 episodes
• Foundation Models — 2× in this paper · explained in 7 episodes
• Generalization — 2× in this paper · explained in 13 episodes
• Guided attention — 2× in this paper · explained in 2 episodes
• In International Conference on Machine Learning — 2× in this paper
• Multimodal Dataset — 2× in this paper · explained in 2 episodes
• Multimodal Inputs — 2× in this paper · explained in 2 episodes
• Multimodal Integration — 2× in this paper · explained in 2 episodes
• Multimodal Learning — 2× in this paper · explained in 2 episodes
• Semantic Understanding — 2× in this paper · explained in 2 episodes
• Ablation — 1× in this paper · explained in 1 episode
• Adjacency Matrix — 1× in this paper · explained in 1 episode
• Consistency — 1× in this paper · explained in 3 episodes
• Cosine Similarity — 1× in this paper · explained in 3 episodes
• Domain Adaptation — 1× in this paper · explained in 5 episodes
• Domain Shift — 1× in this paper · explained in 4 episodes
• Feature Extraction — 1× in this paper · explained in 2 episodes
• GNNs — 1× in this paper · explained in 2 episodes
• Graph Construction — 1× in this paper · explained in 3 episodes
• Graph Neural Network (GNN) — 1× in this paper · explained in 2 episodes
• Modular Components — 1× in this paper · explained in 2 episodes
• Multi-modal Inputs — 1× in this paper · explained in 2 episodes
• Optimal Transport — 1× in this paper · explained in 5 episodes
• Structural Reasoning — 1× in this paper · explained in 2 episodes
• Transformer Architecture — 1× in this paper · explained in 2 episodes
• Verification — 1× in this paper · explained in 2 episodes

Sources

• BoQ: A Place is Worth a Bag of Learnable Queries
• Tell Me Where You Are: Multimodal LLMs Meet Place Recognition
• NYC-Event-VPR: A Large-Scale High-Resolution Event-Based Visual Place Recognition Dataset in Dense Urban Environments
• Graph Attention Networks

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