IMDb-Face

IMDb-Face is a new large-scale noise-controlled dataset for face recognition research. The dataset contains about 1.7 million faces, 59k identities, which is manually cleaned from 2.0 million raw images. All images are obtained from the IMDb website. A detailed introduction of IMDb-Face can be found in the paper click here. We hope that the IMDb-Face dataset could shed lights on the influences of data noise to the face recognition task, and point to potential labelling strategies to mitigate some of the problems. It could serve as a relatively clean data to facilitate future studies of noises in large-scale face recognition.

IMDb-Face是一款面向人脸识别研究的新型大规模噪声可控数据集。该数据集包含约170万张人脸、5.9万个身份类别，其原始数据源自200万张未处理图像，并经人工清洗提纯。所有图像均采集自IMDb（互联网电影数据库）网站。关于IMDb-Face的详细介绍可参阅对应论文（点击此处查看）。本数据集旨在助力研究者明晰数据噪声对人脸识别任务的影响，并为缓解相关问题的潜在标注策略提供参考方向。同时，该数据集可作为一份相对洁净的基准数据，推动大规模人脸识别场景下噪声相关的后续研究工作。

搜集汇总

背景与挑战

背景概述

IMDb-Face是一个用于人脸识别研究的大规模噪声控制数据集，包含约170万张人脸和59k个身份，数据来自IMDb网站并经过手动清理。该数据集旨在分析数据噪声对人脸识别任务的影响，并提供相对干净的数据以支持未来研究。