标题： 基于Transformer的空间定位：全面综述 显示英文标题

标题： Transformer-based Spatial Grounding: A Comprehensive Survey

摘要： 空间定位，即将自然语言表达与相应的图像区域相关联的过程，由于基于变压器的模型的引入而迅速发展，显著增强了多模态表示和跨模态对齐。 尽管取得了这一进展，该领域仍缺乏对当前方法、数据集使用、评估指标和工业适用性的全面综合。 本文对2018年至2025年的基于变压器的空间定位方法进行了系统的文献综述。 我们的分析确定了主导的模型架构、普遍使用的数据集和广泛采用的评估指标，同时突出了关键的方法趋势和最佳实践。 本研究为研究人员和从业者提供了重要的见解和结构化指导，有助于开发强大、可靠且适用于工业的基于变压器的空间定位模型。 显示英文摘要

摘要： Spatial grounding, the process of associating natural language expressions with corresponding image regions, has rapidly advanced due to the introduction of transformer-based models, significantly enhancing multimodal representation and cross-modal alignment. Despite this progress, the field lacks a comprehensive synthesis of current methodologies, dataset usage, evaluation metrics, and industrial applicability. This paper presents a systematic literature review of transformer-based spatial grounding approaches from 2018 to 2025. Our analysis identifies dominant model architectures, prevalent datasets, and widely adopted evaluation metrics, alongside highlighting key methodological trends and best practices. This study provides essential insights and structured guidance for researchers and practitioners, facilitating the development of robust, reliable, and industry-ready transformer-based spatial grounding models.