The rapid adoption of facial recognition (FR) technology by both government and commercial entities in recent years has raised concerns about civil liberties and privacy. In response, a broad suite of so-called "anti-facial recognition" (AFR) tools has been developed to help users avoid unwanted facial recognition. The set of AFR tools proposed in the last few years is wide-ranging and rapidly evolving, necessitating a step back to consider the broader design space of AFR systems and long-term challenges. This paper aims to fill that gap and provides the first comprehensive analysis of the AFR research landscape. Using the operational stages of FR systems as a starting point, we create a systematic framework for analyzing the benefits and tradeoffs of different AFR approaches. We then consider both technical and social challenges facing AFR tools and propose directions for future research in this field.

翻译：近年来，政府与商业实体对人脸识别技术的快速采用引发了公民隐私与自由方面的担忧。为应对这一问题，研究者开发了一系列被称为"反人脸识别"的工具，旨在帮助用户规避非意愿的人脸识别。过去数年间提出的反人脸识别工具种类繁多且迭代迅速，亟需从整体视角审视该系统的设计空间与长期挑战。本文旨在填补这一空白，首次对反人脸识别研究领域进行系统性分析。以人脸识别系统的运作阶段为切入点，我们构建了一个分析不同反人脸识别方法优势与权衡的框架体系，进而探讨反人脸识别工具面临的技术与社会挑战，并为该领域的未来研究方向提出建议。