LFW

LFW database - Labeled Faces in the Wild. Welcome to Labeled Faces in the Wild, a database of face photographs designed for studying the problem of unconstrained face recognition. The data set contains more than 13,000 images of faces collected from the web. Each face has been labeled with the name of the person pictured. 1680 of the people pictured have two or more distinct photos in the data set. The only constraint on these faces is that they were detected by the Viola-Jones face detector. More details can be found in the technical report below. There are now four different sets of LFW images including the original and three different types of ”aligned” images. The aligned images include ”funneled images” (ICCV 2007), LFW-a, which uses an unpublished method of alignment, and ”deep funneled” images (NIPS 2012). Among these, LFW-a and the deep funneled images produce superior results for most face verification algorithms over the original images and over the funneled images (ICCV 2007).


References in zbMATH (referenced in 62 articles )

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  1. Serna, Ignacio; Morales, Aythami; Fierrez, Julian; Obradovich, Nick: Sensitive loss: improving accuracy and fairness of face representations with discrimination-aware deep learning (2022)
  2. Jiang, Haiyan; Xiong, Haoyi; Wu, Dongrui; Liu, Ji; Dou, Dejing: AgFlow: fast model selection of penalized PCA via implicit regularization effects of gradient flow (2021)
  3. Jun Wang, Yinglu Liu, Yibo Hu, Hailin Shi, Tao Mei: FaceX-Zoo: A PyTorch Toolbox for Face Recognition (2021) arXiv
  4. Liang, Peidong; Likassa, Habte Tadesse; Zhang, Chentao; Guo, Jielong: New robust PCA for outliers and heavy sparse noises’ detection via affine transformation, the (L_\ast, w) and (L_2,1) norms, and spatial weight matrix in high-dimensional images: from the perspective of signal processing (2021)
  5. Liu, Chunlei; Ding, Wenrui; Hu, Yuan; Zhang, Baochang; Liu, Jianzhuang; Guo, Guodong; Doermann, David: Rectified binary convolutional networks with generative adversarial learning (2021)
  6. Li, Yuliang; Wang, Jianguo; Pullman, Benjamin; Bandeira, Nuno; Papakonstantinou, Yannis: Index-based, high-dimensional, cosine threshold querying with optimality guarantees (2021)
  7. Qian, Jianjun; Zhu, Shumin; Wong, Wai Keung; Zhang, Hengmin; Lai, Zhihui; Yang, Jian: Dual robust regression for pattern classification (2021)
  8. Qingzhong Wang, Pengfei Zhang, Haoyi Xiong, Jian Zhao: Face.evoLVe: A High-Performance Face Recognition Library (2021) arXiv
  9. Ruan, Yibang; Xiao, Yanshan; Hao, Zhifeng; Liu, Bo: A nearest-neighbor search model for distance metric learning (2021)
  10. Valk, Marcio; Cybis, Gabriela Bettella: (U)-statistical inference for hierarchical clustering (2021)
  11. Amosov, O. S.; Amosova, S. G.; Zhiganov, S. V.; Ivanov, Yu. S.; Pashchenko, F. F.: Computational method for recognizing situations and objects in the frames of a continuous video stream using deep neural networks for access control systems (2020)
  12. Anirudh, Rushil; Thiagarajan, Jayaraman J.; Kailkhura, Bhavya; Bremer, Peer-Timo: MimicGAN: robust projection onto image manifolds with corruption mimicking (2020)
  13. Dornaika, F.; Khoder, A.: Linear embedding by joint robust discriminant analysis and inter-class sparsity (2020)
  14. Escalante-B., Alberto N.; Wiskott, Laurenz: Improved graph-based SFA: information preservation complements the slowness principle (2020)
  15. Jin, Taisong; Cao, Liujuan; Jie, Feiran; Ji, Rongrong: Link-aware semi-supervised hypergraph (2020)
  16. Likassa, Habte Tadesse: New robust principal component analysis for joint image alignment and recovery via affine transformations, Frobenius and (L_2,1) norms (2020)
  17. Likassa, Habte Tadesse; Xian, Wen; Tang, Xuan: New robust regularized shrinkage regression for high-dimensional image recovery and alignment via affine transformation and Tikhonov regularization (2020)
  18. Valaitis, Vytautas; Marcinkevicius, Virginijus; Jurevicius, Rokas: Learning aerial image similarity using triplet networks (2020)
  19. Görgel, Pelin; Simsek, Ahmet: Face recognition via deep stacked denoising sparse autoencoders (DSDSA) (2019)
  20. He, Lingxiao; Li, Haiqing; Zhang, Qi; Sun, Zhenan: Dynamic feature matching for partial face recognition (2019)

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