DiVA: Diverse Visual Feature Aggregation for Deep Metric Learning
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Yoshua Bengio | Joseph Paul Cohen | Karsten Roth | Bjorn Ommer | Timo Milbich | Samarth Sinha | Homanga Bharadhwaj
[1] Jiwen Lu,et al. Hardness-Aware Deep Metric Learning , 2019, 2019 IEEE/CVF Conference on Computer Vision and Pattern Recognition (CVPR).
[2] Xudong Lin,et al. Deep Adversarial Metric Learning , 2018, 2018 IEEE/CVF Conference on Computer Vision and Pattern Recognition.
[3] James Philbin,et al. FaceNet: A unified embedding for face recognition and clustering , 2015, 2015 IEEE Conference on Computer Vision and Pattern Recognition (CVPR).
[4] Phillip Isola,et al. Contrastive Multiview Coding , 2019, ECCV.
[5] 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).
[6] Michiaki Iwazume,et al. Cavity Filling: Pseudo-Feature Generation for Multi-Class Imbalanced Data Problems in Deep Learning , 2018 .
[7] David Berthelot,et al. Understanding and Improving Interpolation in Autoencoders via an Adversarial Regularizer , 2018, ICLR.
[8] Nikos Komodakis,et al. Unsupervised Representation Learning by Predicting Image Rotations , 2018, ICLR.
[9] Bjorn Ommer,et al. Unsupervised Representation Learning by Discovering Reliable Image Relations , 2019, Pattern Recognit..
[10] Jun Wang,et al. Which Looks Like Which: Exploring Inter-class Relationships in Fine-Grained Visual Categorization , 2014, ECCV.
[11] Aaron C. Courville,et al. Hierarchical Adversarially Learned Inference , 2018, ArXiv.
[12] Paolo Favaro,et al. Unsupervised Learning of Visual Representations by Solving Jigsaw Puzzles , 2016, ECCV.
[13] Paolo Favaro,et al. Boosting Self-Supervised Learning via Knowledge Transfer , 2018, 2018 IEEE/CVF Conference on Computer Vision and Pattern Recognition.
[14] Karsten Roth,et al. Sharing Matters for Generalization in Deep Metric Learning , 2020, IEEE transactions on pattern analysis and machine intelligence.
[15] Geoffrey E. Hinton,et al. A Simple Framework for Contrastive Learning of Visual Representations , 2020, ICML.
[16] Yoshua Bengio,et al. Extracting and composing robust features with denoising autoencoders , 2008, ICML '08.
[17] R Devon Hjelm,et al. Learning Representations by Maximizing Mutual Information Across Views , 2019, NeurIPS.
[18] Xudong Lin,et al. Deep Variational Metric Learning , 2018, ECCV.
[19] Alexander J. Smola,et al. Sampling Matters in Deep Embedding Learning , 2017, 2017 IEEE International Conference on Computer Vision (ICCV).
[20] Pieter Abbeel,et al. InfoGAN: Interpretable Representation Learning by Information Maximizing Generative Adversarial Nets , 2016, NIPS.
[21] Yair Movshovitz-Attias,et al. No Fuss Distance Metric Learning Using Proxies , 2017, 2017 IEEE International Conference on Computer Vision (ICCV).
[22] Horst Possegger,et al. Deep Metric Learning with BIER: Boosting Independent Embeddings Robustly , 2018, IEEE Transactions on Pattern Analysis and Machine Intelligence.
[23] Pietro Perona,et al. The Caltech-UCSD Birds-200-2011 Dataset , 2011 .
[24] Weilin Huang,et al. Deep Metric Learning with Hierarchical Triplet Loss , 2018, ECCV.
[25] Hao-Yu Wu,et al. Classification is a Strong Baseline for Deep Metric Learning , 2018, BMVC.
[26] Björn Ommer,et al. Divide and Conquer the Embedding Space for Metric Learning , 2019, 2019 IEEE/CVF Conference on Computer Vision and Pattern Recognition (CVPR).
[27] Marc Sebban,et al. Metric Learning from Imbalanced Data , 2019, 2019 IEEE 31st International Conference on Tools with Artificial Intelligence (ICTAI).
[28] Ioannis Mitliagkas,et al. Manifold Mixup: Better Representations by Interpolating Hidden States , 2018, ICML.
[29] Matthijs Douze,et al. Deep Clustering for Unsupervised Learning of Visual Features , 2018, ECCV.
[30] Mark Sanderson,et al. Christopher D. Manning, Prabhakar Raghavan, Hinrich Schütze, Introduction to Information Retrieval, Cambridge University Press 2008. ISBN-13 978-0-521-86571-5, xxi + 482 pages , 2010, Natural Language Engineering.
[31] Kaiqi Huang,et al. Beyond Triplet Loss: A Deep Quadruplet Network for Person Re-identification , 2017, 2017 IEEE Conference on Computer Vision and Pattern Recognition (CVPR).
[32] Dawn Song,et al. Using Self-Supervised Learning Can Improve Model Robustness and Uncertainty , 2019, NeurIPS.
[33] Björn Ommer,et al. Improving Spatiotemporal Self-Supervision by Deep Reinforcement Learning , 2018, ECCV.
[34] Jiwen Lu,et al. Discriminative Deep Metric Learning for Face Verification in the Wild , 2014, 2014 IEEE Conference on Computer Vision and Pattern Recognition.
[35] 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).
[36] Luca Antiga,et al. Automatic differentiation in PyTorch , 2017 .
[37] Aymeric Histace,et al. Metric Learning With HORDE: High-Order Regularizer for Deep Embeddings , 2019, 2019 IEEE/CVF International Conference on Computer Vision (ICCV).
[38] Karsten Roth,et al. PADS: Policy-Adapted Sampling for Visual Similarity Learning , 2020, 2020 IEEE/CVF Conference on Computer Vision and Pattern Recognition (CVPR).
[39] Naftali Tishby,et al. Deep learning and the information bottleneck principle , 2015, 2015 IEEE Information Theory Workshop (ITW).
[40] Trevor Darrell,et al. Adversarial Feature Learning , 2016, ICLR.
[41] Kihyuk Sohn,et al. Improved Deep Metric Learning with Multi-class N-pair Loss Objective , 2016, NIPS.
[42] Aaron C. Courville,et al. Adversarially Learned Inference , 2016, ICLR.
[43] Jungmin Lee,et al. Attention-based Ensemble for Deep Metric Learning , 2018, ECCV.
[44] Björn Ommer,et al. CliqueCNN: Deep Unsupervised Exemplar Learning , 2016, NIPS.
[45] Robert Pless,et al. Deep Randomized Ensembles for Metric Learning , 2018, ECCV.
[46] Sergey Ioffe,et al. Batch Normalization: Accelerating Deep Network Training by Reducing Internal Covariate Shift , 2015, ICML.
[47] S. Palmer,et al. A century of Gestalt psychology in visual perception: I. Perceptual grouping and figure-ground organization. , 2012, Psychological bulletin.
[48] Kaiming He,et al. Faster R-CNN: Towards Real-Time Object Detection with Region Proposal Networks , 2015, IEEE Transactions on Pattern Analysis and Machine Intelligence.
[49] Dahua Lin,et al. Unsupervised Feature Learning via Non-Parametric Instance-level Discrimination , 2018, ArXiv.
[50] Kaiming He,et al. Momentum Contrast for Unsupervised Visual Representation Learning , 2019, 2020 IEEE/CVF Conference on Computer Vision and Pattern Recognition (CVPR).
[51] Aapo Hyvärinen,et al. Noise-contrastive estimation: A new estimation principle for unnormalized statistical models , 2010, AISTATS.
[52] Stella X. Yu,et al. Unsupervised Feature Learning via Non-parametric Instance Discrimination , 2018, 2018 IEEE/CVF Conference on Computer Vision and Pattern Recognition.
[53] Nitesh V. Chawla,et al. Editorial: special issue on learning from imbalanced data sets , 2004, SKDD.
[54] 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).
[55] Sergey Levine,et al. Unsupervised Learning via Meta-Learning , 2018, ICLR.
[56] Yang Hua,et al. Ranked List Loss for Deep Metric Learning , 2019, 2019 IEEE/CVF Conference on Computer Vision and Pattern Recognition (CVPR).
[57] Jian Wang,et al. Deep Metric Learning with Angular Loss , 2017, 2017 IEEE International Conference on Computer Vision (ICCV).
[58] 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).
[59] Silvio Savarese,et al. Deep Metric Learning via Lifted Structured Feature Embedding , 2015, 2016 IEEE Conference on Computer Vision and Pattern Recognition (CVPR).
[60] Karsten Roth,et al. MIC: Mining Interclass Characteristics for Improved Metric Learning , 2019, 2019 IEEE/CVF International Conference on Computer Vision (ICCV).
[61] Jimmy Ba,et al. Adam: A Method for Stochastic Optimization , 2014, ICLR.
[62] Bhiksha Raj,et al. SphereFace: Deep Hypersphere Embedding for Face Recognition , 2017, 2017 IEEE Conference on Computer Vision and Pattern Recognition (CVPR).
[63] Jonathan Krause,et al. 3D Object Representations for Fine-Grained Categorization , 2013, 2013 IEEE International Conference on Computer Vision Workshops.
[64] Oriol Vinyals,et al. Representation Learning with Contrastive Predictive Coding , 2018, ArXiv.
[65] Joseph Paul Cohen,et al. Revisiting Training Strategies and Generalization Performance in Deep Metric Learning , 2020, ICML.
[66] Cordelia Schmid,et al. Product Quantization for Nearest Neighbor Search , 2011, IEEE Transactions on Pattern Analysis and Machine Intelligence.
[67] Hongtao Lu,et al. An Adversarial Approach to Hard Triplet Generation , 2018, ECCV.
[68] Laurens van der Maaten,et al. Self-Supervised Learning of Pretext-Invariant Representations , 2019, 2020 IEEE/CVF Conference on Computer Vision and Pattern Recognition (CVPR).
[69] Qi Qian,et al. SoftTriple Loss: Deep Metric Learning Without Triplet Sampling , 2019, 2019 IEEE/CVF International Conference on Computer Vision (ICCV).
[70] Max Welling,et al. Auto-Encoding Variational Bayes , 2013, ICLR.
[71] Christopher D. Manning,et al. Introduction to Information Retrieval , 2010, J. Assoc. Inf. Sci. Technol..