Face Space Representations in Deep Convolutional Neural Networks
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Connor J. Parde | Carlos D. Castillo | Matthew Q. Hill | A. O'Toole | R. Chellappa | C. Castillo | A. O’Toole | A. O’toole
[1] Rama Chellappa,et al. HyperFace: A Deep Multi-Task Learning Framework for Face Detection, Landmark Localization, Pose Estimation, and Gender Recognition , 2019, IEEE Transactions on Pattern Analysis and Machine Intelligence.
[2] Swami Sankaranarayanan,et al. Face recognition accuracy of forensic examiners, superrecognizers, and face recognition algorithms , 2018, Proceedings of the National Academy of Sciences.
[3] A. Young,et al. Are We Face Experts? , 2018, Trends in Cognitive Sciences.
[4] Michael Eickenberg,et al. Seeing it all: Convolutional network layers map the function of the human visual system , 2017, NeuroImage.
[5] Carlos D. Castillo,et al. An All-In-One Convolutional Neural Network for Face Analysis , 2016, 2017 12th IEEE International Conference on Automatic Face & Gesture Recognition (FG 2017).
[6] Martin Wistuba,et al. Harnessing Model Uncertainty for Detecting Adversarial Examples , 2017 .
[7] Ha Hong,et al. Explicit information for category-orthogonal object properties increases along the ventral stream , 2016, Nature Neuroscience.
[8] Gang Hua,et al. Labeled Faces in the Wild: A Survey , 2016 .
[9] Randolph Blake,et al. The Occipital Face Area Is Causally Involved in Facial Viewpoint Perception , 2015, The Journal of Neuroscience.
[10] Marcel A J van Gerven,et al. Deep Neural Networks Reveal a Gradient in the Complexity of Neural Representations across the Ventral Stream , 2015, The Journal of Neuroscience.
[11] Geoffrey E. Hinton,et al. Deep Learning , 2015, Nature.
[12] Kendrick N. Kay,et al. Attention Reduces Spatial Uncertainty in Human Ventral Temporal Cortex , 2015, Current Biology.
[13] Yoshua Bengio,et al. Generative Adversarial Nets , 2014, NIPS.
[14] K. Grill-Spector,et al. The functional architecture of the ventral temporal cortex and its role in categorization , 2014, Nature Reviews Neuroscience.
[15] Daniel L. K. Yamins,et al. Deep Neural Networks Rival the Representation of Primate IT Cortex for Core Visual Object Recognition , 2014, PLoS Comput. Biol..
[16] Ha Hong,et al. Performance-optimized hierarchical models predict neural responses in higher visual cortex , 2014, Proceedings of the National Academy of Sciences.
[17] Rob Fergus,et al. Visualizing and Understanding Convolutional Networks , 2013, ECCV.
[18] Alice J. O'Toole,et al. Comparison of human and computer performance across face recognition experiments , 2014, Image and Vision Computing.
[19] Xiaogang Wang,et al. Hybrid Deep Learning for Face Verification , 2013, 2013 IEEE International Conference on Computer Vision.
[20] Alice J. O'Toole,et al. Comparing face recognition algorithms to humans on challenging tasks , 2012, TAP.
[21] Frank Tong,et al. Prevalence of Selectivity for Mirror-Symmetric Views of Faces in the Ventral and Dorsal Visual Pathways , 2012, The Journal of Neuroscience.
[22] Bruce A. Draper,et al. The Good, the Bad, and the Ugly Face Challenge Problem , 2012, Image and Vision Computing.
[23] A. Burton,et al. Variability in photos of the same face , 2011, Cognition.
[24] Brittany S. Cassidy,et al. Lower-Level Stimulus Features Strongly Influence Responses in the Fusiform Face Area , 2010, Cerebral cortex.
[25] Alice J. O'Toole,et al. Dissociable Neural Patterns of Facial Identity across Changes in Viewpoint , 2010, Journal of Cognitive Neuroscience.
[26] Alice J. O'Toole,et al. FRVT 2006 and ICE 2006 Large-Scale Experimental Results , 2010, IEEE Transactions on Pattern Analysis and Machine Intelligence.
[27] Quoc V. Le,et al. Measuring Invariances in Deep Networks , 2009, NIPS.
[28] Marwan Mattar,et al. Labeled Faces in the Wild: A Database forStudying Face Recognition in Unconstrained Environments , 2008 .
[29] Geoffrey E. Hinton,et al. Visualizing Data using t-SNE , 2008 .
[30] Alice J. O'Toole,et al. Face Recognition Algorithms Surpass Humans Matching Faces Over Changes in Illumination , 2007, IEEE Transactions on Pattern Analysis and Machine Intelligence.
[31] David D. Cox,et al. Opinion TRENDS in Cognitive Sciences Vol.11 No.8 Untangling invariant object recognition , 2022 .
[32] Nasser M. Nasrabadi,et al. Pattern Recognition and Machine Learning , 2006, Technometrics.
[33] M. Giese,et al. Norm-based face encoding by single neurons in the monkey inferotemporal cortex , 2006, Nature.
[34] Kilian Q. Weinberger,et al. Distance Metric Learning for Large Margin Nearest Neighbor Classification , 2005, NIPS.
[35] H. Wilson,et al. fMRI evidence for the neural representation of faces , 2005, Nature Neuroscience.
[36] M. Webster,et al. Adaptation to natural facial categories , 2002, Nature.
[37] Kunihiko Fukushima,et al. Neocognitron: A self-organizing neural network model for a mechanism of pattern recognition unaffected by shift in position , 1980, Biological Cybernetics.
[38] A. O'Toole,et al. Prototype-referenced shape encoding revealed by high-level aftereffects , 2001, Nature Neuroscience.
[39] Richard Hans Robert Hahnloser,et al. Digital selection and analogue amplification coexist in a cortex-inspired silicon circuit , 2000, Nature.
[40] Otto H. MacLin,et al. Figural aftereffects in the perception of faces , 1999, Psychonomic bulletin & review.
[41] S. Edelman,et al. Differential Processing of Objects under Various Viewing Conditions in the Human Lateral Occipital Complex , 1999, Neuron.
[42] Thomas Vetter,et al. Three-dimensional shape and two-dimensional surface reflectance contributions to face recognition: an application of three-dimensional morphing , 1999, Vision Research.
[43] Thomas Vetter,et al. A morphable model for the synthesis of 3D faces , 1999, SIGGRAPH.
[44] Timothy F. Cootes,et al. Active Appearance Models , 1998, ECCV.
[45] Hyeonjoon Moon,et al. The FERET evaluation methodology for face-recognition algorithms , 1997, Proceedings of IEEE Computer Society Conference on Computer Vision and Pattern Recognition.
[46] V. Bruce,et al. Face processing: Human perception and principal components analysis , 1996, Memory & cognition.
[47] Timothy F. Cootes,et al. Active Shape Models-Their Training and Application , 1995, Comput. Vis. Image Underst..
[48] Alice J. O'Toole,et al. Low-dimensional representation of faces in higher dimensions of the face space , 1993 .
[49] T. Valentine. The Quarterly Journal of Experimental Psychology Section A: Human Experimental Psychology a Unified Account of the Effects of Distinctiveness, Inversion, and Race in Face Recognition , 2022 .
[50] M. Turk,et al. Eigenfaces for Recognition , 1991, Journal of Cognitive Neuroscience.
[51] Lawrence D. Jackel,et al. Backpropagation Applied to Handwritten Zip Code Recognition , 1989, Neural Computation.
[52] Alice J. O'Toole,et al. A physical system approach to recognition memory for spatially transformed faces , 1988, Neural Networks.
[53] L Sirovich,et al. Low-dimensional procedure for the characterization of human faces. , 1987, Journal of the Optical Society of America. A, Optics and image science.
[54] Takayuki Ito,et al. Neocognitron: A neural network model for a mechanism of visual pattern recognition , 1983, IEEE Transactions on Systems, Man, and Cybernetics.
[55] S Hollander,et al. Recognition memory for typical and unusual faces. , 1979, Journal of experimental psychology. Human learning and memory.
[56] R. Malpass,et al. Recognition for faces of own and other race. , 1969, Journal of personality and social psychology.
[57] D. Hubel,et al. Receptive fields, binocular interaction and functional architecture in the cat's visual cortex , 1962, The Journal of physiology.
[58] J. Maxwell. XVIII.—Experiments on Colour, as perceived by the Eye, with Remarks on Colour-Blindness , 1857, Transactions of the Royal Society of Edinburgh.
[59] Thomas Young,et al. II. The Bakerian Lecture. On the theory of light and colours , 1802, Philosophical Transactions of the Royal Society of London.