人脸数据集不太好直接找到，实际在 github上的insightface里有汇总。
说明：
MS1M-IBUG ： MS1M V1
MS1M-ArcFace ： MS1M V2
MS1M-RetinaFace ： MS1M V3
以下信息来自于网站 ：https://github.com/deepinsight/insightface/tree/master/recognition/_datasets_
Face Recognition Datasets
Training Datasets (Updating)
CASIA-Webface (10K ids/0.5M images) [1]
CelebA (10K ids/0.2M images) [2]
UMDFace (8K ids/0.37M images) [3]
VGG2 (9K ids/3.31M images) [4]
MS1M-IBUG (85K ids/3.8M images) [5,6]
MS1M-ArcFace (85K ids/5.8M images) [5,7]
MS1M-RetinaFace
Baidu (code:8eb3)
Asian-Celeb (94K ids/2.8M images)[8]
Glint360K (360K ids/17M images)[17]
Baidu (code:o3az)
magnet uri: magnet:?xt=urn:btih:E5F46EE502B9E76DA8CC3A0E4F7C17E4000C7B1E&dn=glint360k
Glint-Mini (91K ids/5.2M images)[17]
Baidu (code:10m5)
DeepGlint (181K ids/6.75M images) [8]
WebFace260M [18]
IMDB-Face (59K ids/1.7M images) [9]
Celeb500k (500K ids/50M images) [10]
MegaFace(train) (672K ids/4.7M images) [11]
Baidu (code:5f8m)
Validation Datasets
CFP-FP (500 ids/7K images/7K pairs)[12]
AgeDB-30 (570 ids/12,240 images/6K pairs)[13,6]
LFW (5749 ids/13233 images/6K pairs)[14]
CALFW (5749 ids/13233 images/6K pairs)[15]
CPLFW (5749 ids/13233 images/6K pairs)[16]
Image Test Datasets
MegaFace
testsuite: GDrive
IJB (IJB-B, IJB-C)
testsuite: GDrive
TrillionPairs
NIST
Video Test Datasets
YTF
IQIYI
Reference
[1] Dong Yi, Zhen Lei, Shengcai Liao, Stan Z. Li. Learning Face Representation from Scratch. arXiv:1411.7923, 2014.
[2] Ziwei Liu, Ping Luo, Xiaogang Wang, Xiaoou Tang. Deep Learning Face Attributes in the Wild, ICCV, 2015.
[3] Bansal Ankan, Nanduri Anirudh, Castillo Carlos D, Ranjan Rajeev, Chellappa, Rama. UMDFaces: An Annotated Face Dataset for Training Deep Networks, arXiv:1611.01484v2, 2016.
[4] Qiong Cao, Li Shen, Weidi Xie, Omkar M. Parkhi, Andrew Zisserman. VGGFace2: A dataset for recognising faces across pose and age. FG, 2018.
[5] Yandong Guo, Lei Zhang, Yuxiao Hu, Xiaodong He, Jianfeng Gao. Ms-celeb-1m: A dataset and benchmark for large-scale face recognition. ECCV, 2016.
[6] Jiankang Deng, Yuxiang Zhou, Stefanos Zafeiriou. Marginal loss for deep face recognition, CVPRW, 2017.
[7] Jiankang Deng, Jia Guo, Stefanos Zafeiriou. Arcface: Additive angular margin loss for deep face recognition, arXiv:1801.07698, 2018.
[8] Trillionpairs
[9] Wang Fei, Chen Liren, Li Cheng, Huang Shiyao, Chen Yanjie, Qian Chen, Loy, Chen Change. The Devil of Face Recognition is in the Noise, ECCV, 2018.
[10] Cao Jiajiong, Li Yingming, Zhang Zhongfei, Celeb-500K: A Large Training Dataset for Face Recognition, ICIP, 2018.
[11] Nech Aaron, Kemelmacher-Shlizerman Ira, Level Playing Field For Million Scale Face Recognition, CVPR, 2017.
[12] Sengupta Soumyadip, Chen Jun-Cheng, Castillo Carlos, Patel Vishal M, Chellappa Rama, Jacobs David W, Frontal to profile face verification in the wild, WACV, 2016.
[13] Moschoglou, Stylianos and Papaioannou, Athanasios and Sagonas, Christos and Deng, Jiankang and Kotsia, Irene and Zafeiriou, Stefanos, Agedb: the first manually collected, in-the-wild age database, CVPRW, 2017.
[14] Gary B. Huang, Manu Ramesh, Tamara Berg, and Erik Learned-Miller. Labeled Faces in the Wild: A Database for Studying Face Recognition in Unconstrained Environments, 2007.
[15] Zheng Tianyue, Deng Weihong, Hu Jiani, Cross-age lfw: A database for studying cross-age face recognition in unconstrained environments, arXiv:1708.08197, 2017.
[16] Zheng, Tianyue, and Weihong Deng. Cross-Pose LFW: A Database for Studying Cross-Pose Face Recognition in Unconstrained Environments, 2018.
[17] An, Xiang and Zhu, Xuhan and Xiao, Yang and Wu, Lan and Zhang, Ming and Gao, Yuan and Qin, Bin and Zhang, Debing and Fu Ying. Partial FC: Training 10 Million Identities on a Single Machine, arxiv:2010.05222, 2020.
[18] Zheng Zhu, Guan Huang, Jiankang Deng, Yun Ye, Junjie Huang, Xinze Chen, Jiagang Zhu, Tian Yang, Jiwen Lu, Dalong Du, Jie Zhou. WebFace260M: A Benchmark Unveiling the Power of Million-scale Deep Face Recognition