面向无数据持续无监督域自适应行人重识别的颜色提示方法
Color Prompting for Data-Free Continual Unsupervised Domain Adaptive Person Re-Identification
AI总结：
针对持续无监督域自适应行人重识别的遗忘与隐私问题，提出基于轻量提示网络的颜色提示方法CoP，通过学习颜色分布实现风格迁移，无数据场景下抗遗忘与新域泛化效果优于图像回放方法。
摘要：
无监督域自适应行人重识别（Re-ID）方法通过生成伪监督信息减轻了数据标注的负担。然而，现实世界中的Re-ID系统伴随着持续累积的数据流，同时需要更强的自适应能力和抗遗忘能力。基于图像回放的方法以有限的额外存储解决了遗忘问题，但存在隐私泄露风险。在本研究中，我们提出了一种用于无数据持续无监督域自适应行人Re-ID的颜色提示（Color Prompting, CoP）方法。具体而言，我们采用一个轻量级提示网络，在进行Re-ID训练的同时拟合当前任务的颜色分布。随后对于后续到来的新任务，已学习到的颜色分布可作为颜色风格迁移引导，将图像转换为过往任务的风格。CoP能够为过往任务实现准确的颜色风格还原，同时具备充足的数据多样性，与图像回放方法相比展现出更优异的抗遗忘效果。此外，在仅提供少量无标注图像的情况下，CoP在快速适配新域方面表现出强大的泛化性能。大量实验表明，经过持续训练流程后，所提出的CoP方法在已见域和未见域上的平均rank-1指标分别比回放方法提升6.7%和8.1%。本研究的源代码已公开发布于https://github.com/vimar-gu/ColorPromptReID。
英文摘要：
Unsupervised domain adaptive person re-identification (Re-ID) methods alleviate the burden of data annotation through generating pseudo supervision messages. However, real-world Re-ID systems, with continuously accumulating data streams, simultaneously demand more robust adaptation and anti-forgetting capabilities. Methods based on image rehearsal addresses the forgetting issue with limited extra storage but carry the risk of privacy leakage. In this work, we propose a Color Prompting (CoP) method for data-free continual unsupervised domain adaptive person Re-ID. Specifically, we employ a light-weighted prompter network to fit the color distribution of the current task together with Re-ID training. Then for the incoming new tasks, the learned color distribution serves as color style transfer guidance to transfer the images into past styles. CoP achieves accurate color style recovery for past tasks with adequate data diversity, leading to superior anti-forgetting effects compared with image rehearsal methods. Moreover, CoP demonstrates strong generalization performance for fast adaptation into new domains, given only a small amount of unlabeled images. Extensive experiments demonstrate that after the continual training pipeline the proposed CoP achieves 6.7% and 8.1% average rank-1 improvements over the replay method on seen and unseen domains, respectively. The source code for this work is publicly available in https://github.com/vimar-gu/ColorPromptReID.
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。
