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Our goal is to design architectures that retain the groundbreaking performance of CNNs for landmark localization and at the same time are lightweight, compact and suitable for applications with limited computational resources.
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Annotated facial landmarks in the wild: A large-scale, real-world database for facial landmark localization
M. Köstinger, P. Wohlhart, P. M. Roth, and H. Bischof · 2011
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Lecture 6.5-rmsprop: Divide the gradient by a running average of its recent magnitude
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X. Cao, Y. Wei, F. Wen, and J. Sun · 2014
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M. Courbariaux, Y. Bengio, and J.-P. David · 2014
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Joint training of a convolutional network and a graphical model for human pose estimation
J. J. Tompson, A. Jain, Y. LeCun, and C. Bregler · 2014
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Deeppose: Human pose estimation via deep neural networks
A. Toshev and C. Szegedy · 2014
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Binaryconnect: Training deep neural networks with binary weights during propagations
M. Courbariaux, Y. Bengio, and J.-P. David · 2015
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Batch normalization: Accelerating deep network training by reducing internal covariate shift
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Fixed point quantization of deep convolutional networks
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J. Long, E. Shelhamer, and T. Darrell · 2015
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Going deeper with convolutions
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Deepercut: A deeper, stronger, and faster multi-person pose estimation model
E. Insafutdinov, L. Pishchulin, B. Andres, M. Andriluka, and B. Schiele · 2016
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Large-pose face alignment via cnn-based dense 3d model fitting
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Deep neural networks are robust to weight binarization and other non-linear distortions
P. Merolla, R. Appuswamy, J. Arthur, S. K. Esser, and D. Modha · 2016
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A. Newell, K. Yang, and J. Deng · 2016
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R. Ranjan, V. M. Patel, and R. Chellappa · 2016
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N. Zhang, E. Shelhamer, Y. Gao, and T. Darrell · 2015
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Convolutional aggregation of local evidence for large pose face alignment
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Human pose estimation via convolutional part heatmap regression
A. Bulat and G. Tzimiropoulos · 2016
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Two-stage convolutional part heatmap regression for the 1st 3d face alignment in the wild (3dfaw) challenge
A. Bulat and G. Tzimiropoulos · 2016
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Binarized neural networks: Training deep neural networks with weights and activations constrained to+ 1 or-1
M. Courbariaux, I. Hubara, D. Soudry, R. El-Yaniv, and Y. Bengio · 2016
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Deep residual learning for image recognition
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Convolutional pose machines
S.-E. Wei, V. Ramakrishna, T. Kanade, and Y. Sheikh · 2016
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Aggregated residual transformations for deep neural networks
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Wide residual networks
S. Zagoruyko and N. Komodakis · 2016
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Dorefa-net: Training low bitwidth convolutional neural networks with low bitwidth gradients
S. Zhou, Y. Wu, Z. Ni, X. Zhou, H. Wen, and Y. Zou · 2016
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Face alignment across large poses: A 3d solution
X. Zhu, Z. Lei, X. Liu, H. Shi, and S. Z. Li · 2016
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An all-in-one convolutional neural network for face analysis
R. Ranjan, S. Sankaranarayanan, C. D. Castillo, and R. Chellappa · 2017
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Inception-v4, inception-resnet and the impact of residual connections on learning
C. Szegedy, S. Ioffe, V. Vanhoucke, and A. A. Alemi · 2017
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