DialogueVPR: Towards Conversational Visual Place Recognition

• URL: http://arxiv.org/abs/2607.14115v1
• Date: Fri, 08 May 2026 12:04:43 GMT
• Title: DialogueVPR: Towards Conversational Visual Place Recognition
• Abstract summary: We propose a paradigm shift to reasoning retrieval and introduce Dialogue Place Recognition (DlgPR)<n>DlgPR casts localization as an interactive, dialogue-driven reasoning process.<n>We present DlgQuest-Cities, the first large-scale dialogue-based benchmark for place recognition.
• Score: 47.182753191840185
• License: http://arxiv.org/licenses/nonexclusive-distrib/1.0/
• Abstract: Inspired by how humans communicate spatial information, language-guided geo-localization has gained significant traction for its intuitive and practical value. Despite this progress, most methods still rely on a static, one-shot retrieval paradigm, which fails to handle the ambiguity and incompleteness inherent in real-world natural language descriptions. We propose a paradigm shift to reasoning retrieval and introduce Dialogue Place Recognition (DlgPR), which casts localization as an interactive, dialogue-driven reasoning process. To support this new task, we present DlgQuest-Cities, the first large-scale dialogue-based benchmark for place recognition, and a unified reasoning framework that couples a cross-modal multi-level retriever with an intelligent questioner, DQ-pilot. DQ-pilot is trained in a curriculum: supervised fine-tuning on a curated DQ-cities-20k subset followed by reinforcement refinement on a harder DQ-cities-10k split via GRPO. Two task-aligned metrics guide learning: a Discriminative Difficulty Index (DDI) for curriculum sampling and a Positional Retrieval Gain (PRG) reward that directly measures retrieval improvement induced by a question. Experiments show this reasoning-based approach significantly outperforms baselines. The code and model are available at https://github.com/Graysonggg/DlgPR.

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