EMID

EMID是由华东师范大学开发的一个新颖数据集，专注于音乐与图像的情感匹配，旨在促进听觉-视觉跨模态任务如生成和检索。该数据集不同于现有方法，主要关注语义关联或粗略划分的情感关系，而是强调使用先进的13维情感模型来确保音乐与图像之间的情感一致性。通过将情感对齐纳入数据集，它旨在建立与人类感知理解紧密对齐的配对，从而提高听觉-视觉跨模态任务的性能。此外，设计了一个名为EMI-Adapter的辅助模块，以优化现有的跨模态对齐方法。数据集的应用领域包括心理治疗等，旨在解决跨模态对齐中的情感匹配问题。

EMID is a novel dataset developed by East China Normal University, focusing on emotion matching between music and images, aiming to facilitate auditory-visual cross-modal tasks such as generation and retrieval. Unlike existing approaches that primarily focus on semantic association or coarsely categorized emotional relationships, this dataset emphasizes the utilization of a state-of-the-art 13-dimensional emotion model to ensure emotional consistency between music and images. By incorporating emotion alignment into the dataset, it aims to establish pairs that closely align with human perceptual understanding, thereby improving the performance of auditory-visual cross-modal tasks. Additionally, an auxiliary module named EMI-Adapter is designed to optimize existing cross-modal alignment methods. The dataset has application scenarios including psychotherapy and other fields, and is intended to address the emotion matching problem in cross-modal alignment.