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We propose a novel approach for estimating the difficulty and transferability of supervised classification tasks.
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How transferable are features in deep neural networks?
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Hossein Azizpour, Ali Sharif Razavian, Josephine Sullivan, Atsuto Maki, and Stefan Carlsson · 2015
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Mxnet: A flexible and efficient machine learning library for heterogeneous distributed systems
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The loss surfaces of multilayer networks
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Deep learning face attributes in the wild
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Rasmus Rothe, Radu Timofte, and Luc Van Gool · 2015
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Towards unified depth and semantic prediction from a single image
Peng Wang, Xiaohui Shen, Zhe Lin, Scott Cohen, Brian Price, and Alan L Yuille · 2015
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Harrison Edwards and Amos Storkey · 2016
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MS-Celeb-1M: A dataset and benchmark for large scale face recognition
Yandong Guo, Lei Zhang, Yuxiao Hu, Xiaodong He, and Jianfeng Gao · 2016
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Deep residual learning for image recognition
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Learning deep representation for imbalanced classification
Chen Huang, Yining Li, Chen Change Loy, and Xiaoou Tang · 2016
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Deep cross residual learning for multitask visual recognition
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Asymmetric multi-task learning based on task relatedness and loss
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Cross-stitch networks for multi-task learning
Ishan Misra, Abhinav Shrivastava, Abhinav Gupta, and Martial Hebert · 2016
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Moon: A mixed objective optimization network for the recognition of facial attributes
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Exploring disentangled feature representation beyond face identification
Yu Liu, Fangyin Wei, Jing Shao, Lu Sheng, Junjie Yan, and Xiaogang Wang · 2018
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Detach and adapt: Learning cross-domain disentangled deep representation
Yen-Cheng Liu, Yu-Ying Yeh, Tzu-Chien Fu, Sheng-De Wang, Wei-Chen Chiu, and Yu-Chiang Frank Wang · 2018
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Exploring the limits of weakly supervised pretraining
Dhruv Mahajan, Ross Girshick, Vignesh Ramanathan, Kaiming He, Manohar Paluri, Yixuan Li, Ashwin Bharambe, and Laurens van der Maaten · 2018
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Learning pose-aware models for pose-invariant face recognition in the wild
I. Masi, F. J. Chang, J. Choi, S. Harel, J. Kim, K. Kim, J. Leksut, S. Rawls, Y. Wu, T. Hassner, W. AbdAlmageed, G. Medioni, L. P. Morency, P. Natarajan, and R. Nevatia · 2018
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Variational continual learning
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A survey of transfer learning
Karl Weiss, Taghi M Khoshgoftaar, and DingDing Wang · 2016
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Faceposenet: Making a case for landmark-free face alignment
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Class rectification hard mining for imbalanced deep learning
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Attributes for improved attributes: A multi-task network utilizing implicit and explicit relationships for facial attribute classification
Emily M Hand and Rama Chellappa · 2017
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On face segmentation, face swapping, and face perception
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Extreme 3D face reconstruction: Looking past occlusions
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Cosface: Large margin cosine loss for deep face recognition
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Zero-shot learning-a comprehensive evaluation of the good, the bad and the ugly
Yongqin Xian, Christoph H Lampert, Bernt Schiele, and Zeynep Akata · 2018
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Transfer learning via learning to transfer
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Taskonomy: Disentangling task transfer learning
Amir R Zamir, Alexander Sax, William Shen, Leonidas J Guibas, Jitendra Malik, and Silvio Savarese · 2018
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A modulation module for multi-task learning with applications in image retrieval
Xiangyun Zhao, Haoxiang Li, Xiaohui Shen, Xiaodan Liang, and Ying Wu · 2018
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Task2Vec: Task embedding for meta-learning
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The information complexity of learning tasks, their structure and their distance
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Regularized learning for domain adaptation under label shifts
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Deep, landmark-free fame: Face alignment, modeling, and expression estimation
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On measuring the iconicity of a face
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Large-scale weakly-supervised pre-training for video action recognition
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Registration-free face-ssd: Single shot analysis of smiles, facial attributes, and affect in the wild
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Face-specific data augmentation for unconstrained face recognition
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Toward understanding catastrophic forgetting in continual learning
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Hyperface: A deep multi-task learning framework for face detection, landmark localization, pose estimation, and gender recognition
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Beyond sharing weights for deep domain adaptation
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