面向视觉定位的短语解耦跨模态层级匹配与渐进式位置校正
Phrase Decoupling Cross-Modal Hierarchical Matching and Progressive Position Correction for Visual Grounding
AI总结：
针对现有视觉定位方法忽略不同层级文本图像特征关联对跨模态匹配促进作用的问题，提出短语解耦跨模态层级匹配与渐进式位置校正方法，经多数据集实验验证性能优于当前最优方法。
摘要：
视觉定位凭借其在各类视觉语言任务中的广泛应用受到了广泛关注。尽管视觉定位已取得显著研究进展，但现有方法忽略了不同层级的文本与图像特征之间的关联对跨模态匹配的促进作用。本文提出一种短语解耦跨模态层级匹配与渐进式位置校正视觉定位方法。该方法首先通过解耦后的句子短语生成掩码，并构建文本与图像层级匹配机制，凸显不同层级间的关联在跨模态匹配中的作用。此外，基于该层级匹配机制定义了相应的目标对象位置渐进校正策略，以实现对文本描述目标对象的精准定位。该方法可随着目标对象文本描述确定性的提升，持续优化调整目标对象的边界框位置。这一设计探究了不同层级特征间的关联，凸显了目标对象及其位置相关特征在目标定位中的作用。所提方法通过实验在不同数据集上得到验证，且通过与当前最优（state-of-the-art）方法的性能对比，验证了其优越性。
英文摘要：
Visual grounding has attracted wide attention thanks to its broad application in various visual language tasks. Although visual grounding has made significant research progress, existing methods ignore the promotion effect of the association between text and image features at different hierarchies on cross-modal matching. This paper proposes a Phrase Decoupling Cross-Modal Hierarchical Matching and Progressive Position Correction Visual Grounding method. It first generates a mask through decoupled sentence phrases, and a text and image hierarchical matching mechanism is constructed, highlighting the role of association between different hierarchies in cross-modal matching. In addition, a corresponding target object position progressive correction strategy is defined based on the hierarchical matching mechanism to achieve accurate positioning for the target object described in the text. This method can continuously optimize and adjust the bounding box position of the target object as the certainty of the text description of the target object improves. This design explores the association between features at different hierarchies and highlights the role of features related to the target object and its position in target positioning. The proposed method is validated on different datasets through experiments, and its superiority is verified by the performance comparison with the state-of-the-art methods.
机构、总结、中文摘要均由AI分析而来，可能存在错误，请以论文正文为准。
