Fetching the paper…
Reading the bibliography…
Detecting anomalous faces has important applications.
On the generalized distance in statistics
Mahalanobis, Prasanta Chandra · 1936
Earlier work this paper cites.
Low-dimensional procedure for the characterization of human faces
Sirovich, Lawrence and Kirby, Michael · 1987
Earlier work this paper cites.
Autoencoders, minimum description length and helmholtz free energy
Hinton, Geoffrey E and Zemel, Richard S · 1994
Earlier work this paper cites.
Support vector method for novelty detection
Schölkopf, Bernhard, Williamson, Robert C, Smola, Alex J, Shawe-Taylor, John, and Platt, John C · 2000
Earlier work this paper cites.
Rapid object detection using a boosted cascade of simple features
Viola, Paul and Jones, Michael · 2001
Earlier work this paper cites.
Outlier modeling in image matching
Hasler, D, Sbaiz, L, Susstrunk, S, and Vetterli, M · 2003
Earlier work this paper cites.
A real-time computer vision system for detecting defects in textile fabrics
Mak, K L, Peng, P, and Lau, H Y K · 2005
Earlier work this paper cites.
Reducing the dimensionality of data with neural networks
Hinton, Geoffrey E and Salakhutdinov, Ruslan R · 2006
Earlier work this paper cites.
Defect detection in textile fabric images using wavelet transforms and independent component analysis
Serdaroglu, A, Ertuzun, A, and Ercil, A · 2006
Earlier work this paper cites.
Size, power and false discovery rates
Efron, Bradley · 2007
Earlier work this paper cites.
Learning deep architectures for ai
Bengio, Yoshua et al · 2009
Earlier work this paper cites.
Anomaly Detection: A Survey
Chandola, Varun, Banerjee, Arindam, and Kumar, Vipin · 2009
Cited alongside, same era.
Regularization paths for generalized linear models via coordinate descent
Friedman, Jerome, Hastie, Trevor, and Tibshirani, Robert · 2010
Cited alongside, same era.
Stacked Denoising Autoencoders: Learning Useful Representations in a Deep Network with a Local Denoising Criterion
Vincent, Pascal, Larochelle, Hugo, Lajoie, Isabelle, Bengio, Yoshua, and Manzagol, Pierre-Antoine · 2010
Cited alongside, same era.
Unsupervised detection of abnormalities in medical images using salient features
Alpert, Sharon and Kisilev, Pavel · 2014
Cited alongside, same era.
Generative Adversarial Networks
Goodfellow, Ian J, Pouget-Abadie, Jean, Mehdi, Mirza, Xu, Bing, Warde-Farley, David, Ozair, Sherjil, Courville, Aaron, and Bengio, Yoshua · 2014
Cited alongside, same era.
Auto-Encoding Variational Bayes
Kingma, Diederik P and Welling, Max · 2014
An Anomaly Detection Approach to Face Spoofing Detection: A New Formulation and Evaluation Protocol
Arashloo, Shervin Rahimzadeh, Kittler, Josef, and Christmas, William · 2017
Later among the works it cites.
Began: Boundary equilibrium generative adversarial networks
Berthelot, David, Schumm, Tom, and Metz, Luke · 2017
Later among the works it cites.
Vggface2: A dataset for recognising faces across pose and age
Cao, Qiong, Shen, Li, Xie, Weidi, Parkhi, Omkar M, and Zisserman, Andrew · 2017
Later among the works it cites.
Learning Diverse Image Colorization
Deshpande, Aditya, Lu, Jiajun, Yeh, Mao-Chuang, Chong, Min Jin, and Forsyth, David · 2017
Later among the works it cites.
Fader Networks: Manipulating Images by Sliding Attributes
Lample, Guillaume, Zeghidour, Neil, Usunier, Nicolas, Bordes, Antoine, Denoyer, Ludovic, and Ronzato, MarcAurelio · 2017
Later among the works it cites.
alphaXiv searches the wider corpus for related work and actual follow-ups.
alphaXiv is searching for related work…
Cited alongside, same era.
Deep learning face attributes in the wild
Liu, Ziwei, Luo, Ping, Wang, Xiaogang, and Tang, Xiaoou · 2015
Cited alongside, same era.
Context Encoders: Feature Learning by Inpainting
Pathak, Deepak, Krähenbühl, Philipp, Donahue, Jeff, Darrell, Trevor, and Efros, Alexei A · 2016
Cited alongside, same era.
Attribute2Image: Conditional Image Generation from Visual Attributes
Yan, Xinchen, Yang, Jimei, Sohn, Kihyuk, and Lee, Honglak · 2016
Cited alongside, same era.
Deep structured energy based models for anomaly detection
Zhai, Shuangfei, Cheng, Yu, Lu, Weining, and Zhang, Zhongfei · 2016
Cited alongside, same era.
Unsupervised anomaly detection with generative adversarial networks to guide marker discovery
Schlegl, Thomas, Seeböck, Philipp, Waldstein, Sebastian M, Schmidt-Erfurth, Ursula, and Langs, Georg · 2017
Later among the works it cites.
Deep Sets
Zaheer, Manzil, Kottur, Satwik, Ravanbakhsh, Siamak, Poczos, Barnabas, Salakhutdinov, Ruslan R, and Smola, Alexander J · 2017
Later among the works it cites.
Anomaly detection with generative adversarial networks, 2018
Deecke, Lucas, Vandermeulen, Robert, Ruff, Lukas, Mandt, Stephan, and Kloft, Marius · 2018
Closest in time.
Semi-supervised outlier detection using generative and adversary framework, 2018
Jindong Gu, Matthias Schubert and Tresp, Volker · 2018
Closest in time.
Novelty detection with GAN, 2018
Kliger, Mark and Fleishman, Shachar · 2018
Closest in time.