Abstract
Text-based person re-identification (Re-ID) is a challenging topic in the field of complex multimodal analysis, its ultimate aim is to recognize specific pedestrians by scrutinizing attributes/natural language descriptions. Despite the wide range of applicable areas such as security surveillance, video retrieval, person tracking, and social media analytics, there is a notable absence of comprehensive reviews dedicated to summarizing the text-based person Re-ID from a technical perspective. To address this gap, we propose to introduce a taxonomy spanning Evaluation, Strategy, Architecture, and Optimization dimensions, providing a comprehensive survey of the text-based person Re-ID task. We start by laying the groundwork for text-based person Re-ID, elucidating fundamental concepts related to attribute/natural language-based identification. Then a thorough examination of existing benchmark datasets and metrics is presented. Subsequently, we further delve into prevalent feature extraction strategies employed in text-based person Re-ID research, followed by a concise summary of common network architectures within the domain. Prevalent loss functions utilized for model optimization and modality alignment in text-based person Re-ID are also scrutinized. To conclude, we offer a concise summary of our findings, pinpointing challenges in text-based person Re-ID. In response to these challenges, we outline potential avenues for future open-set text-based person Re-ID and present a baseline architecture for text-based pedestrian image generation-guided re-identification(TBPGR).
Abstract (translated)
基于文本的人身识别（Re-ID）是复杂多模态分析领域的一个具有挑战性的课题，其最终目标是通过对属性/自然语言描述的审查来识别特定的行人。尽管应用领域很广，如安全监控、视频检索、行人追踪和社会媒体分析，但缺乏对基于文本的人身识别的全面综述是一个显著的不足。为了填补这个空白，我们提议引入一个评估、策略、架构和优化维度的分类法，全面调查基于文本的人身识别（Re-ID）任务。我们首先阐明了基于文本的人身识别的基础知识，阐明了与属性/自然语言-基于识别相关的核心概念。接着，我们详细介绍了现有基准数据集和指标。随后，我们深入研究了文本中常用的人身识别特征提取策略，接着是对该领域中常见的网络架构的简要概述。我们还对用于模型优化和模式对齐的现有损失函数进行了审查。总之，我们给出了我们调查的简要总结，指出了基于文本的人身识别的挑战。为了应对这些挑战，我们提出了未来可以开放设置的基于文本的人身识别的可能途径，并提出了基于文本行人图像生成引导的人身识别（TBPGR）的基准架构。
URL
https://arxiv.org/abs/2408.00096
