GeoBridge：用于生成式图像地理定位的解耦语义条件机制

中文摘要 AI 辅助

多模态大语言模型（MLLM）主要通过优化地理线索推理能力推动了图像地理定位的发展，但其推理结果解码为坐标的环节却相对滞后。为地理编码API预测地名是离散且有损的：它忽略了图像证据，还将多粒度语义压缩为粗粒度查找。本文认为瓶颈已从模型的推理内容转变为推理结果向连续、几何感知解码器的表示方式。我们提出GeoBridge，一种角色解耦的条件机制，将冻结的语义MLLM与冻结的黎曼流匹配头连接，用于生成球体上的坐标。核心障碍是角色冲突：用离散语义标签监督条件会使条件表示偏向类别判别几何，与生成头所需的平滑流形不匹配。GeoBridge将语义监督与条件接口解耦：通过单独的投影生成冻结头所需的连续条件，注入地理先验而不干扰球形解码器。在IM2GPS3K数据集上，GeoBridge在25/200/750公里阈值下的准确率达到38.67/52.89/70.37，在这些与精度相关的尺度上优于地名转API管道和推理增强的直接预测。GeoBridge是一种解码侧算法贡献，与思维链推理正交且互补，代码将公开提供。

英文摘要

Multimodal large language models (MLLMs) have advanced image geolocalization mainly by improving how they reason about geographic cues. How that reasoning isdecoded into coordinates, however, has lagged behind. Predicting a place name for a geocoding API is discrete and lossy: it ignores image evidence and collapses multi-granular semantics into a coarse lookup. We argue that the bottleneck has shifted from what a model reasons to how that reasoning is represented for a continuous, geometry-aware decoder. We present GeoBridge, a role-decoupled conditioning mechanism that connects a frozen semantic MLLM to a frozen Riemannian flow-matching head that generates coordinates on the sphere. The central obstacle is arole conflict: supervising the condition with discrete semantic labels biases its representation toward class-discriminative geometry, at odds with the smooth manifold the generative head requires. GeoBridge keeps the semantic supervision decoupled from the condition interface: a separate projection forms the continuous condition the frozen head expects, injecting geographic priors without disturbing the spherical decoder. On IM2GPS3K, GeoBridge reaches 38.67/52.89/70.37 at the 25/200/750 km thresholds, improving over a place-name-to-API pipeline and reasoning-augmented direct prediction at these precision-relevant scales. GeoBridge is a decode-side algorithmic contribution, orthogonal and complementary to chain-of-thought reasoning. Code will be made publicly available.

发表机构

• University of Chinese Academy of Sciences（中国科学院大学）
• School of Advanced Interdisciplinary Sciences（先进交叉科学学院）
• School of Electronic, Electrical and Communication Engineering（电子电气与通信工程学院）
• Shenzhen Institutes of Advanced Technology（深圳先进技术研究院）

机构由 AI 辅助整理，请以论文原文为准。