Deep convolutional neural networks (CNNs) based approaches are the state-of-the-art in various computer vision tasks, including face recognition. Considerable research effort is currently being directed towards further improving deep CNNs by focusing on more powerful mo... View more
 A. Alahi, K. Goel, V. Ramanathan, A. Robicquet, L. Fei-Fei, and S. Savarese. Social LSTM: Human trajectory prediction in crowded spaces. In Proceedings of the IEEE Conference on Computer Vision and Pattern Recognition, pages 961-971, 2016.
 V. Badrinarayanan, A. Handa, and R. Cipolla. Segnet: A deep convolutional encoder-decoder architecture for robust semantic pixel-wise labelling. arXiv preprint arXiv:1505.07293, 2015.
 N. D. Bruce, C. Catton, and S. Janjic. A deeper look at saliency: feature contrast, semantics, and beyond. In Proceedings of the IEEE Conference on Computer Vision and Pattern Recognition, pages 516-524, 2016.
 S. Chaib, H. Yao, Y. Gu, and M. Amrani. Deep feature extraction and combination for remote sensing image classification based on pre-trained cnn models. In Ninth International Conference on Digital Image Processing (ICDIP 2017), pages 104203D-104203D. International Society for Optics and Photonics, 2017.
 K. Chatfield, K. Simonyan, A. Vedaldi, and A. Zisserman. Return of the devil in the details: Delving deep into convolutional nets. arXiv preprint arXiv:1405.3531, 2014.
 J.-C. Chen, S. Sankaranarayanan, V. M. Patel, and R. Chellappa. Unconstrained face verification using fisher vectors computed from frontalized faces. In Biometrics Theory, Applications and Systems (BTAS), 2015 IEEE 7th International Conference on, pages 1-8. IEEE, 2015.
 L.-C. Chen, G. Papandreou, I. Kokkinos, K. Murphy, and A. L. Yuille. Semantic image segmentation with deep convolutional nets and fully connected crfs. arXiv preprint arXiv:1412.7062, 2014.
 S. Dodge and L. Karam. Understanding how image quality affects deep neural networks. In Quality of Multimedia Experience (QoMEX), 2016 Eighth International Conference on, pages 1-6. IEEE, 2016.
 A. Dosovitskiy, J. T. Springenberg, M. Riedmiller, and T. Brox. Discriminative unsupervised feature learning with convolutional neural networks. In Advances in Neural Information Processing Systems, pages 766-774, 2014.
 S. Gidaris and N. Komodakis. Object detection via a multi-region and semantic segmentation-aware cnn model. In Proceedings of the IEEE International Conference on Computer Vision, pages 1134-1142, 2015.