Personalized Convolution for Face Recognition
暂无分享,去创建一个
S. Shan | Xilin Chen | Meina Kan | Shuzhe Wu | Chunrui Han
[1] Yonghyun Kim,et al. BroadFace: Looking at Tens of Thousands of People at Once for Face Recognition , 2020, ECCV.
[2] Yonghyun Kim,et al. GroupFace: Learning Latent Groups and Constructing Group-Based Representations for Face Recognition , 2020, 2020 IEEE/CVF Conference on Computer Vision and Pattern Recognition (CVPR).
[3] Feiyue Huang,et al. CurricularFace: Adaptive Curriculum Learning Loss for Deep Face Recognition , 2020, 2020 IEEE/CVF Conference on Computer Vision and Pattern Recognition (CVPR).
[4] Chunhua Shen,et al. Conditional Convolutions for Instance Segmentation , 2020, ECCV.
[5] Sixue Gong,et al. Jointly De-Biasing Face Recognition and Demographic Attribute Estimation , 2019, ECCV.
[6] Wei Liu,et al. Occlusion Robust Face Recognition Based on Mask Learning With Pairwise Differential Siamese Network , 2019, 2019 IEEE/CVF International Conference on Computer Vision (ICCV).
[7] Bong-Nam Kang,et al. Attentional Feature-Pair Relation Networks for Accurate Face Recognition , 2019, 2019 IEEE/CVF International Conference on Computer Vision (ICCV).
[8] Kai Zhao,et al. RegularFace: Deep Face Recognition via Exclusive Regularization , 2019, 2019 IEEE/CVF Conference on Computer Vision and Pattern Recognition (CVPR).
[9] Jiwen Lu,et al. UniformFace: Learning Deep Equidistributed Representation for Face Recognition , 2019, 2019 IEEE/CVF Conference on Computer Vision and Pattern Recognition (CVPR).
[10] Ling Shao,et al. Interpretable and Generalizable Deep Image Matching with Adaptive Convolutions , 2019, ArXiv.
[11] Hao Wang,et al. Decorrelated Adversarial Learning for Age-Invariant Face Recognition , 2019, 2019 IEEE/CVF Conference on Computer Vision and Pattern Recognition (CVPR).
[12] Shiguang Shan,et al. Face Recognition with Contrastive Convolution , 2018, ECCV.
[13] Shuicheng Yan,et al. Look Across Elapse: Disentangled Representation Learning and Photorealistic Cross-Age Face Synthesis for Age-Invariant Face Recognition , 2018, AAAI.
[14] Yonghyun Kim,et al. Pairwise Relational Networks for Face Recognition , 2018, ECCV.
[15] Li Shen,et al. Comparator Networks , 2018, ECCV.
[16] Xiaogang Wang,et al. FaceID-GAN: Learning a Symmetry Three-Player GAN for Identity-Preserving Face Synthesis , 2018, 2018 IEEE/CVF Conference on Computer Vision and Pattern Recognition.
[17] Jiwen Lu,et al. Context-Aware Local Binary Feature Learning for Face Recognition , 2018, IEEE Transactions on Pattern Analysis and Machine Intelligence.
[18] Mei Wang,et al. Deep Face Recognition: A Survey , 2018, Neurocomputing.
[19] Anil K. Jain,et al. IARPA Janus Benchmark - C: Face Dataset and Protocol , 2018, 2018 International Conference on Biometrics (ICB).
[20] Xing Ji,et al. CosFace: Large Margin Cosine Loss for Deep Face Recognition , 2018, 2018 IEEE/CVF Conference on Computer Vision and Pattern Recognition.
[21] S. Zafeiriou,et al. ArcFace: Additive Angular Margin Loss for Deep Face Recognition , 2018, 2019 IEEE/CVF Conference on Computer Vision and Pattern Recognition (CVPR).
[22] Antoni B. Chan,et al. Incorporating Side Information by Adaptive Convolution , 2017, International Journal of Computer Vision.
[23] Omkar M. Parkhi,et al. VGGFace2: A Dataset for Recognising Faces across Pose and Age , 2017, 2018 13th IEEE International Conference on Automatic Face & Gesture Recognition (FG 2018).
[24] Yi Yang,et al. Recursive Spatial Transformer (ReST) for Alignment-Free Face Recognition , 2017, 2017 IEEE International Conference on Computer Vision (ICCV).
[25] Sheng Tang,et al. Scale-Adaptive Convolutions for Scene Parsing , 2017, 2017 IEEE International Conference on Computer Vision (ICCV).
[26] Xiaoming Liu,et al. Disentangled Representation Learning GAN for Pose-Invariant Face Recognition , 2017, 2017 IEEE Conference on Computer Vision and Pattern Recognition (CVPR).
[27] Anil K. Jain,et al. IARPA Janus Benchmark-B Face Dataset , 2017, 2017 IEEE Conference on Computer Vision and Pattern Recognition Workshops (CVPRW).
[28] Anil K. Jain,et al. Face Search at Scale , 2017, IEEE Transactions on Pattern Analysis and Machine Intelligence.
[29] Bhiksha Raj,et al. SphereFace: Deep Hypersphere Embedding for Face Recognition , 2017, 2017 IEEE Conference on Computer Vision and Pattern Recognition (CVPR).
[30] Kihyuk Sohn,et al. Towards Large-Pose Face Frontalization in the Wild , 2017, 2017 IEEE International Conference on Computer Vision (ICCV).
[31] Nenghai Yu,et al. StyleBank: An Explicit Representation for Neural Image Style Transfer , 2017, 2017 IEEE Conference on Computer Vision and Pattern Recognition (CVPR).
[32] Tal Hassner,et al. Regressing Robust and Discriminative 3D Morphable Models with a Very Deep Neural Network , 2016, 2017 IEEE Conference on Computer Vision and Pattern Recognition (CVPR).
[33] Meng Yang,et al. Large-Margin Softmax Loss for Convolutional Neural Networks , 2016, ICML.
[34] Luca Bertinetto,et al. Learning feed-forward one-shot learners , 2016, NIPS.
[35] Gérard G. Medioni,et al. Pose-Aware Face Recognition in the Wild , 2016, 2016 IEEE Conference on Computer Vision and Pattern Recognition (CVPR).
[36] Luc Van Gool,et al. Dynamic Filter Networks , 2016, NIPS.
[37] Yu Qiao,et al. Joint Face Detection and Alignment Using Multitask Cascaded Convolutional Networks , 2016, IEEE Signal Processing Letters.
[38] Tal Hassner,et al. Do We Really Need to Collect Millions of Faces for Effective Face Recognition? , 2016, ECCV.
[39] Ramakant Nevatia,et al. Face recognition using deep multi-pose representations , 2016, 2016 IEEE Winter Conference on Applications of Computer Vision (WACV).
[40] Swami Sankaranarayanan,et al. Triplet Similarity Embedding for Face Verification , 2016, ArXiv.
[41] Dacheng Tao,et al. Robust Face Recognition via Multimodal Deep Face Representation , 2015, IEEE Transactions on Multimedia.
[42] Rama Chellappa,et al. Unconstrained face verification using deep CNN features , 2015, 2016 IEEE Winter Conference on Applications of Computer Vision (WACV).
[43] Anil K. Jain,et al. Pushing the frontiers of unconstrained face detection and recognition: IARPA Janus Benchmark A , 2015, 2015 IEEE Conference on Computer Vision and Pattern Recognition (CVPR).
[44] Lior Wolf,et al. A Dynamic Convolutional Layer for short rangeweather prediction , 2015, 2015 IEEE Conference on Computer Vision and Pattern Recognition (CVPR).
[45] James Philbin,et al. FaceNet: A unified embedding for face recognition and clustering , 2015, 2015 IEEE Conference on Computer Vision and Pattern Recognition (CVPR).
[46] Xiaogang Wang,et al. DeepID3: Face Recognition with Very Deep Neural Networks , 2015, ArXiv.
[47] Xiaogang Wang,et al. Deeply learned face representations are sparse, selective, and robust , 2014, 2015 IEEE Conference on Computer Vision and Pattern Recognition (CVPR).
[48] Shengcai Liao,et al. Learning Face Representation from Scratch , 2014, ArXiv.
[49] Xiaogang Wang,et al. Deep Learning Face Representation from Predicting 10,000 Classes , 2014, 2014 IEEE Conference on Computer Vision and Pattern Recognition.
[50] Xiaogang Wang,et al. Deep Learning Face Representation by Joint Identification-Verification , 2014, NIPS.
[51] 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.
[52] Matti Pietikäinen,et al. Learning Discriminant Face Descriptor , 2014, IEEE Transactions on Pattern Analysis and Machine Intelligence.
[53] Jian Sun,et al. Bayesian Face Revisited: A Joint Formulation , 2012, ECCV.
[54] Jun Guo,et al. Extended SRC: Undersampled Face Recognition via Intraclass Variant Dictionary , 2012, IEEE Transactions on Pattern Analysis and Machine Intelligence.
[55] Lei Zhang,et al. Sparse representation or collaborative representation: Which helps face recognition? , 2011, 2011 International Conference on Computer Vision.
[56] Tal Hassner,et al. Face recognition in unconstrained videos with matched background similarity , 2011, CVPR 2011.
[57] Jian Sun,et al. Face recognition with learning-based descriptor , 2010, 2010 IEEE Computer Society Conference on Computer Vision and Pattern Recognition.
[58] Jie Chen,et al. Fusing Local Patterns of Gabor Magnitude and Phase for Face Recognition , 2010, IEEE Transactions on Image Processing.
[59] Dima Damen,et al. Recognizing linked events: Searching the space of feasible explanations , 2009, 2009 IEEE Conference on Computer Vision and Pattern Recognition.
[60] A. Yang,et al. Robust Face Recognition via Sparse Representation , 2009, IEEE Transactions on Pattern Analysis and Machine Intelligence.
[61] Marwan Mattar,et al. Labeled Faces in the Wild: A Database forStudying Face Recognition in Unconstrained Environments , 2008 .
[62] Xiaoyang Tan,et al. Enhanced Local Texture Feature Sets for Face Recognition Under Difficult Lighting Conditions , 2007, IEEE Transactions on Image Processing.
[63] Matti Pietikäinen,et al. Face Description with Local Binary Patterns: Application to Face Recognition , 2006, IEEE Transactions on Pattern Analysis and Machine Intelligence.
[64] Wen Gao,et al. Local Gabor binary pattern histogram sequence (LGBPHS): a novel non-statistical model for face representation and recognition , 2005, Tenth IEEE International Conference on Computer Vision (ICCV'05) Volume 1.
[65] Shuicheng Yan,et al. Graph embedding: a general framework for dimensionality reduction , 2005, 2005 IEEE Computer Society Conference on Computer Vision and Pattern Recognition (CVPR'05).
[66] Yuxiao Hu,et al. Face recognition using Laplacianfaces , 2005, IEEE Transactions on Pattern Analysis and Machine Intelligence.
[67] Chengjun Liu,et al. Gabor feature based classification using the enhanced fisher linear discriminant model for face recognition , 2002, IEEE Trans. Image Process..
[68] Alex Pentland,et al. Beyond eigenfaces: probabilistic matching for face recognition , 1998, Proceedings Third IEEE International Conference on Automatic Face and Gesture Recognition.
[69] David J. Kriegman,et al. Eigenfaces vs. Fisherfaces: Recognition Using Class Specific Linear Projection , 1996, ECCV.
[70] Xiaoming Liu,et al. Supplementary Material for ”Improving Face Recognition from Hard Samples via Distribution Distillation Loss” , 2020 .
[71] Andrew Zisserman,et al. Deep Face Recognition , 2015, BMVC.
[72] Erik Learned-Miller,et al. Labeled Faces in the Wild : Updates and New Reporting Procedures , 2014 .
[73] Wen Gao,et al. Histogram of Gabor Phase Patterns (HGPP): A Novel Object Representation Approach for Face Recognition , 2007, IEEE Transactions on Image Processing.
[74] Luc Van Gool,et al. European conference on computer vision (ECCV) , 2006, eccv 2006.
[75] P. Belhumeur,et al. Eigenfaces vs . Fisherfaces : Recognition Using Class Speci c Linear Projection , 2001 .
[76] A. Pentland,et al. Beyond Linear Eigenspaces: Bayesian Matching for Face Recognition , 1998 .
[77] M. Turk,et al. Eigenfaces for Recognition , 1991, Journal of Cognitive Neuroscience.