Circle Loss: A Unified Perspective of Pair Similarity Optimization
暂无分享,去创建一个
[1] Xing Ji,et al. CosFace: Large Margin Cosine Loss for Deep Face Recognition , 2018, 2018 IEEE/CVF Conference on Computer Vision and Pattern Recognition.
[2] James Philbin,et al. FaceNet: A unified embedding for face recognition and clustering , 2015, 2015 IEEE Conference on Computer Vision and Pattern Recognition (CVPR).
[3] Jian Cheng,et al. NormFace: L2 Hypersphere Embedding for Face Verification , 2017, ACM Multimedia.
[4] Victor S. Lempitsky,et al. Learning Deep Embeddings with Histogram Loss , 2016, NIPS.
[5] Sergey Ioffe,et al. Batch Normalization: Accelerating Deep Network Training by Reducing Internal Covariate Shift , 2015, ICML.
[6] Jian Wang,et al. Deep Metric Learning with Angular Loss , 2017, 2017 IEEE International Conference on Computer Vision (ICCV).
[7] Stefanos Zafeiriou,et al. ArcFace: Additive Angular Margin Loss for Deep Face Recognition , 2018, 2019 IEEE/CVF Conference on Computer Vision and Pattern Recognition (CVPR).
[8] Matthew R. Scott,et al. Multi-Similarity Loss With General Pair Weighting for Deep Metric Learning , 2019, 2019 IEEE/CVF Conference on Computer Vision and Pattern Recognition (CVPR).
[9] Silvio Savarese,et al. Deep Metric Learning via Lifted Structured Feature Embedding , 2015, 2016 IEEE Conference on Computer Vision and Pattern Recognition (CVPR).
[10] Qi Tian,et al. Scalable Person Re-identification: A Benchmark , 2015, 2015 IEEE International Conference on Computer Vision (ICCV).
[11] Bhiksha Raj,et al. SphereFace: Deep Hypersphere Embedding for Face Recognition , 2017, 2017 IEEE Conference on Computer Vision and Pattern Recognition (CVPR).
[12] Carlos D. Castillo,et al. Frontal to profile face verification in the wild , 2016, 2016 IEEE Winter Conference on Applications of Computer Vision (WACV).
[13] Xiaogang Wang,et al. Deep Learning Face Representation from Predicting 10,000 Classes , 2014, 2014 IEEE Conference on Computer Vision and Pattern Recognition.
[14] Qi Tian,et al. Beyond Part Models: Person Retrieval with Refined Part Pooling , 2017, ECCV.
[15] Weilin Huang,et al. Deep Metric Learning with Hierarchical Triplet Loss , 2018, ECCV.
[16] Yann LeCun,et al. Dimensionality Reduction by Learning an Invariant Mapping , 2006, 2006 IEEE Computer Society Conference on Computer Vision and Pattern Recognition (CVPR'06).
[17] Yu Qiao,et al. A Discriminative Feature Learning Approach for Deep Face Recognition , 2016, ECCV.
[18] Lucas Beyer,et al. In Defense of the Triplet Loss for Person Re-Identification , 2017, ArXiv.
[19] Xiaogang Wang,et al. AdaCos: Adaptively Scaling Cosine Logits for Effectively Learning Deep Face Representations , 2019, 2019 IEEE/CVF Conference on Computer Vision and Pattern Recognition (CVPR).
[20] Marwan Mattar,et al. Labeled Faces in the Wild: A Database forStudying Face Recognition in Unconstrained Environments , 2008 .
[21] Xiong Chen,et al. Learning Discriminative Features with Multiple Granularities for Person Re-Identification , 2018, ACM Multimedia.
[22] Horst Possegger,et al. Deep Metric Learning with BIER: Boosting Independent Embeddings Robustly , 2018, IEEE Transactions on Pattern Analysis and Machine Intelligence.
[23] Stefanie Jegelka,et al. Deep Metric Learning via Facility Location , 2016, 2017 IEEE Conference on Computer Vision and Pattern Recognition (CVPR).
[24] Carlos D. Castillo,et al. L2-constrained Softmax Loss for Discriminative Face Verification , 2017, ArXiv.
[25] Meng Yang,et al. Large-Margin Softmax Loss for Convolutional Neural Networks , 2016, ICML.
[26] Lanqing He,et al. Softmax Dissection: Towards Understanding Intra- and Inter-clas Objective for Embedding Learning , 2020, AAAI.
[27] Kihyuk Sohn,et al. Improved Deep Metric Learning with Multi-class N-pair Loss Objective , 2016, NIPS.
[28] Ira Kemelmacher-Shlizerman,et al. The MegaFace Benchmark: 1 Million Faces for Recognition at Scale , 2015, 2016 IEEE Conference on Computer Vision and Pattern Recognition (CVPR).
[29] Jonathan Krause,et al. 3D Object Representations for Fine-Grained Categorization , 2013, 2013 IEEE International Conference on Computer Vision Workshops.
[30] Longhui Wei,et al. Person Transfer GAN to Bridge Domain Gap for Person Re-identification , 2017, 2018 IEEE/CVF Conference on Computer Vision and Pattern Recognition.
[31] Pietro Perona,et al. The Caltech-UCSD Birds-200-2011 Dataset , 2011 .
[32] Jungmin Lee,et al. Attention-based Ensemble for Deep Metric Learning , 2018, ECCV.
[33] Yuxiao Hu,et al. MS-Celeb-1M: A Dataset and Benchmark for Large-Scale Face Recognition , 2016, ECCV.
[34] Yann LeCun,et al. Learning a similarity metric discriminatively, with application to face verification , 2005, 2005 IEEE Computer Society Conference on Computer Vision and Pattern Recognition (CVPR'05).
[35] Jian Cheng,et al. Additive Margin Softmax for Face Verification , 2018, IEEE Signal Processing Letters.
[36] Zhedong Zheng,et al. Joint Discriminative and Generative Learning for Person Re-Identification , 2019, 2019 IEEE/CVF Conference on Computer Vision and Pattern Recognition (CVPR).
[37] Tal Hassner,et al. Face recognition in unconstrained videos with matched background similarity , 2011, CVPR 2011.
[38] Anil K. Jain,et al. IARPA Janus Benchmark - C: Face Dataset and Protocol , 2018, 2018 International Conference on Biometrics (ICB).
[39] Alexander J. Smola,et al. Sampling Matters in Deep Embedding Learning , 2017, 2017 IEEE International Conference on Computer Vision (ICCV).
[40] Nir Ailon,et al. Deep Metric Learning Using Triplet Network , 2014, SIMBAD.
[41] Jian Sun,et al. Deep Residual Learning for Image Recognition , 2015, 2016 IEEE Conference on Computer Vision and Pattern Recognition (CVPR).
[42] Wei Zhang,et al. Heated-Up Softmax Embedding , 2018, ArXiv.