GridFace: Face Rectification via Learning Local Homography Transformations
暂无分享,去创建一个
Jian Sun | Erjin Zhou | Zhimin Cao | Jian Sun | Zhimin Cao | Erjin Zhou
[1] Yoshua Bengio,et al. What regularized auto-encoders learn from the data-generating distribution , 2012, J. Mach. Learn. Res..
[2] Ming Yang,et al. DeepFace: Closing the Gap to Human-Level Performance in Face Verification , 2014, 2014 IEEE Conference on Computer Vision and Pattern Recognition.
[3] Harri Valpola,et al. Denoising Source Separation , 2005, J. Mach. Learn. Res..
[4] Xiangyu Zhu,et al. High-fidelity Pose and Expression Normalization for face recognition in the wild , 2015, 2015 IEEE Conference on Computer Vision and Pattern Recognition (CVPR).
[5] Yoshua Bengio,et al. Generative Adversarial Nets , 2014, NIPS.
[6] Gaurav Sharma,et al. CP-mtML: Coupled Projection Multi-Task Metric Learning for Large Scale Face Retrieval , 2016, 2016 IEEE Conference on Computer Vision and Pattern Recognition (CVPR).
[7] Dimitris N. Metaxas,et al. Reconstruction-Based Disentanglement for Pose-Invariant Face Recognition , 2017, 2017 IEEE International Conference on Computer Vision (ICCV).
[8] Marwan Mattar,et al. Labeled Faces in the Wild: A Database forStudying Face Recognition in Unconstrained Environments , 2008 .
[9] Dongqing Zhang,et al. Neural Aggregation Network for Video Face Recognition , 2016, 2017 IEEE Conference on Computer Vision and Pattern Recognition (CVPR).
[10] Xiaogang Wang,et al. Deep Learning Identity-Preserving Face Space , 2013, 2013 IEEE International Conference on Computer Vision.
[11] Bo Huang,et al. Toward End-to-End Face Recognition Through Alignment Learning , 2017, IEEE Signal Processing Letters.
[12] Takeo Kanade,et al. Multi-PIE , 2008, 2008 8th IEEE International Conference on Automatic Face & Gesture Recognition.
[13] Qiong Cao,et al. Template Adaptation for Face Verification and Identification , 2016, 2017 12th IEEE International Conference on Automatic Face & Gesture Recognition (FG 2017).
[14] William T. Freeman,et al. Synthesizing Normalized Faces from Facial Identity Features , 2017, 2017 IEEE Conference on Computer Vision and Pattern Recognition (CVPR).
[15] Yoshua Bengio,et al. Plug & Play Generative Networks: Conditional Iterative Generation of Images in Latent Space , 2016, 2017 IEEE Conference on Computer Vision and Pattern Recognition (CVPR).
[16] Gang Hua,et al. Supervised Transformer Network for Efficient Face Detection , 2016, ECCV.
[17] Rama Chellappa,et al. Pose-Robust Face Verification by Exploiting Competing Tasks , 2017, 2017 IEEE Winter Conference on Applications of Computer Vision (WACV).
[18] Ran He,et al. Beyond Face Rotation: Global and Local Perception GAN for Photorealistic and Identity Preserving Frontal View Synthesis , 2017, 2017 IEEE International Conference on Computer Vision (ICCV).
[19] 김준모,et al. Rotating Your Face Using Multi-task Deep Neural Network , 2015 .
[20] Xiao Zhang,et al. Range Loss for Deep Face Recognition with Long-Tailed Training Data , 2016, 2017 IEEE International Conference on Computer Vision (ICCV).
[21] Gérard G. Medioni,et al. Pose-Aware Face Recognition in the Wild , 2016, 2016 IEEE Conference on Computer Vision and Pattern Recognition (CVPR).
[22] Ming Yang,et al. Web-scale training for face identification , 2014, 2015 IEEE Conference on Computer Vision and Pattern Recognition (CVPR).
[23] Simon Lucey,et al. Inverse Compositional Spatial Transformer Networks , 2016, 2017 IEEE Conference on Computer Vision and Pattern Recognition (CVPR).
[24] Yu Liu,et al. Quality Aware Network for Set to Set Recognition , 2017, 2017 IEEE Conference on Computer Vision and Pattern Recognition (CVPR).
[25] Michael Möller,et al. Learning Proximal Operators: Using Denoising Networks for Regularizing Inverse Imaging Problems , 2017, 2017 IEEE International Conference on Computer Vision (ICCV).
[26] Tal Hassner,et al. Face recognition in unconstrained videos with matched background similarity , 2011, CVPR 2011.
[27] Haibin Ling,et al. Cross-age face verification by coordinating with cross-face age verification , 2015, 2015 IEEE Conference on Computer Vision and Pattern Recognition (CVPR).
[28] Anil K. Jain,et al. Unconstrained Face Recognition: Identifying a Person of Interest From a Media Collection , 2014, IEEE Transactions on Information Forensics and Security.
[29] Yi Yang,et al. Recursive Spatial Transformer (ReST) for Alignment-Free Face Recognition , 2017, 2017 IEEE International Conference on Computer Vision (ICCV).
[30] Xiaoming Liu,et al. Coefficients Pose-Variant Input Recogni 8 on Engine Frontalized Output Generator FF-GAN D Discriminator Extreme Pose Input Frontalized Output , 2017 .
[31] Carlos D. Castillo,et al. Triplet probabilistic embedding for face verification and clustering , 2016, 2016 IEEE 8th International Conference on Biometrics Theory, Applications and Systems (BTAS).
[32] Xiaogang Wang,et al. Deep Learning Face Representation by Joint Identification-Verification , 2014, NIPS.
[33] Xiaogang Wang,et al. Deep Learning Face Representation from Predicting 10,000 Classes , 2014, 2014 IEEE Conference on Computer Vision and Pattern Recognition.
[34] Dumitru Erhan,et al. Going deeper with convolutions , 2014, 2015 IEEE Conference on Computer Vision and Pattern Recognition (CVPR).
[35] Andrew Zisserman,et al. Spatial Transformer Networks , 2015, NIPS.
[36] Xiaogang Wang,et al. Multi-View Perceptron: a Deep Model for Learning Face Identity and View Representations , 2014, NIPS.
[37] Tal Hassner,et al. Do We Really Need to Collect Millions of Faces for Effective Face Recognition? , 2016, ECCV.
[38] Andrew Zisserman,et al. Deep Face Recognition , 2015, BMVC.
[39] James Philbin,et al. FaceNet: A unified embedding for face recognition and clustering , 2015, 2015 IEEE Conference on Computer Vision and Pattern Recognition (CVPR).
[40] Lucas Theis,et al. Amortised MAP Inference for Image Super-resolution , 2016, ICLR.
[41] David W. Jacobs,et al. WarpNet: Weakly Supervised Matching for Single-View Reconstruction , 2016, 2016 IEEE Conference on Computer Vision and Pattern Recognition (CVPR).
[42] Xiaogang Wang,et al. Deeply learned face representations are sparse, selective, and robust , 2014, 2015 IEEE Conference on Computer Vision and Pattern Recognition (CVPR).
[43] Yu Qiao,et al. A Discriminative Feature Learning Approach for Deep Face Recognition , 2016, ECCV.
[44] Tal Hassner,et al. Effective face frontalization in unconstrained images , 2014, 2015 IEEE Conference on Computer Vision and Pattern Recognition (CVPR).
[45] Yuxiao Hu,et al. MS-Celeb-1M: A Dataset and Benchmark for Large-Scale Face Recognition , 2016, ECCV.
[46] Xiaoming Liu,et al. Disentangled Representation Learning GAN for Pose-Invariant Face Recognition , 2017, 2017 IEEE Conference on Computer Vision and Pattern Recognition (CVPR).
[47] Matthias Zwicker,et al. Deep Mean-Shift Priors for Image Restoration , 2017, NIPS.