Uncertainty and Robustness in Deep Visual Learning
Active Adversarial Domain Adaptation-
[pdf]
[bibtex]@InProceedings{Su_2019_CVPR_Workshops,
author = {Su, Jong-Chyi and Tsai, Yi-Hsuan and Sohn, Kihyuk and Liu, Buyu and Maji, Subhransu and Chandraker, Manmohan},
title = {Active Adversarial Domain Adaptation},
booktitle = {Proceedings of the IEEE/CVF Conference on Computer Vision and Pattern Recognition (CVPR) Workshops},
month = {June},
year = {2019}
}
Learn To Be Uncertain: Leveraging Uncertain Labels In Chest X-rays With Bayesian Neural Networks-
[pdf]
[bibtex]@InProceedings{Yang_2019_CVPR_Workshops,
author = {Yang, Hao-Yu and Yang, Junling and Pan, Yue and Cao, Kunlin and Song, Qi and Gao, Feng and Yin, Youbing},
title = {Learn To Be Uncertain: Leveraging Uncertain Labels In Chest X-rays With Bayesian Neural Networks},
booktitle = {Proceedings of the IEEE/CVF Conference on Computer Vision and Pattern Recognition (CVPR) Workshops},
month = {June},
year = {2019}
}
Modeling assumptions and evaluation schemes: On the assessment of deep latent variable models-
[pdf]
[bibtex]@InProceedings{Butepage_2019_CVPR_Workshops,
author = {Butepage, Judith and Poklukar, Petra and Kragic, Danica},
title = {Modeling assumptions and evaluation schemes: On the assessment of deep latent variable models},
booktitle = {Proceedings of the IEEE/CVF Conference on Computer Vision and Pattern Recognition (CVPR) Workshops},
month = {June},
year = {2019}
}
On the Sensitivity of Adversarial Robustness to Input Data Distributions-
[pdf]
[bibtex]@InProceedings{Ding_2019_CVPR_Workshops,
author = {Weiguang Ding, Gavin and Yik Chau Lui, Kry and Jin, Xiaomeng and Wang, Luyu and Huang, Ruitong},
title = {On the Sensitivity of Adversarial Robustness to Input Data Distributions},
booktitle = {Proceedings of the IEEE/CVF Conference on Computer Vision and Pattern Recognition (CVPR) Workshops},
month = {June},
year = {2019}
}
Empirical Study of MC-Dropout in Various Astronomical Observing Conditions-
[pdf]
[bibtex]@InProceedings{Kennamer_2019_CVPR_Workshops,
author = {Kennamer, Noble and Ihler, Alex and Kirkby, David},
title = {Empirical Study of MC-Dropout in Various Astronomical Observing Conditions},
booktitle = {Proceedings of the IEEE/CVF Conference on Computer Vision and Pattern Recognition (CVPR) Workshops},
month = {June},
year = {2019}
}
Multi-Task Learning based on Separable Formulation of Depth Estimation and its Uncertainty-
[pdf]
[bibtex]@InProceedings{Asai_2019_CVPR_Workshops,
author = {Asai, Akari and Ikami, Daiki and Aizawa, Kiyoharu},
title = {Multi-Task Learning based on Separable Formulation of Depth Estimation and its Uncertainty},
booktitle = {Proceedings of the IEEE/CVF Conference on Computer Vision and Pattern Recognition (CVPR) Workshops},
month = {June},
year = {2019}
}
Automated Label Noise Identification for Facial Attribute Recognition-
[pdf]
[bibtex]@InProceedings{Speth_2019_CVPR_Workshops,
author = {Speth, Jeremy and Hand, Emily M.},
title = {Automated Label Noise Identification for Facial Attribute Recognition},
booktitle = {Proceedings of the IEEE/CVF Conference on Computer Vision and Pattern Recognition (CVPR) Workshops},
month = {June},
year = {2019}
}
Incremental Learning with Unlabeled Data in the Wild-
[pdf]
[bibtex]@InProceedings{Lee_2019_CVPR_Workshops,
author = {Lee, Kibok and Lee, Kimin and Shin, Jinwoo and Lee, Honglak},
title = {Incremental Learning with Unlabeled Data in the Wild},
booktitle = {Proceedings of the IEEE/CVF Conference on Computer Vision and Pattern Recognition (CVPR) Workshops},
month = {June},
year = {2019}
}
Uncertainty Based Detection and Relabeling of Noisy Image Labels-
[pdf]
[bibtex]@InProceedings{Kohler_2019_CVPR_Workshops,
author = {Kohler, Jan M. and Autenrieth, Maximilian and Beluch, William H.},
title = {Uncertainty Based Detection and Relabeling of Noisy Image Labels},
booktitle = {Proceedings of the IEEE/CVF Conference on Computer Vision and Pattern Recognition (CVPR) Workshops},
month = {June},
year = {2019}
}
Measuring Calibration in Deep Learning-
[pdf]
[bibtex]@InProceedings{Nixon_2019_CVPR_Workshops,
author = {Nixon, Jeremy and Dusenberry, Michael W. and Zhang, Linchuan and Jerfel, Ghassen and Tran, Dustin},
title = {Measuring Calibration in Deep Learning},
booktitle = {Proceedings of the IEEE/CVF Conference on Computer Vision and Pattern Recognition (CVPR) Workshops},
month = {June},
year = {2019}
}
Benchmarking Sampling-based Probabilistic Object Detectors-
[pdf]
[bibtex]@InProceedings{Miller_2019_CVPR_Workshops,
author = {Miller, Dimity and Sunderhauf, Niko and Zhang, Haoyang and Hall, David and Dayoub, Feras},
title = {Benchmarking Sampling-based Probabilistic Object Detectors},
booktitle = {Proceedings of the IEEE/CVF Conference on Computer Vision and Pattern Recognition (CVPR) Workshops},
month = {June},
year = {2019}
}
f-VAEGAN-D2: A Feature Generating Framework for Any-Shot Learning-
[pdf]
[bibtex]@InProceedings{Xian_2019_CVPR_Workshops,
author = {Xian, Yongqin and Sharma, Saurabh and Schiele, Bernt and Akata, Zeynep},
title = {f-VAEGAN-D2: A Feature Generating Framework for Any-Shot Learning},
booktitle = {Proceedings of the IEEE/CVF Conference on Computer Vision and Pattern Recognition (CVPR) Workshops},
month = {June},
year = {2019}
}
Structured Aleatoric Uncertainty in Human Pose Estimation-
[pdf]
[bibtex]@InProceedings{Gundavarapu_2019_CVPR_Workshops,
author = {Gundavarapu, Nitesh B. and Srivastava, Divyansh and Mitra, Rahul and Sharma, Abhishek and Jain, Arjun},
title = {Structured Aleatoric Uncertainty in Human Pose Estimation},
booktitle = {Proceedings of the IEEE/CVF Conference on Computer Vision and Pattern Recognition (CVPR) Workshops},
month = {June},
year = {2019}
}
Generalized Zero-Shot Learning via Aligned Variational Autoencoders-
[pdf]
[bibtex]@InProceedings{Schonfeld_2019_CVPR_Workshops,
author = {Schonfeld, Edgar and Ebrahimi, Sayna and Sinha, Samarth and Darrell, Trevor and Akata, Zeynep},
title = {Generalized Zero-Shot Learning via Aligned Variational Autoencoders},
booktitle = {Proceedings of the IEEE/CVF Conference on Computer Vision and Pattern Recognition (CVPR) Workshops},
month = {June},
year = {2019}
}
Why ReLU networks yield high-confidence predictions far away from the training data and how to mitigate the problem-
[pdf]
[bibtex]@InProceedings{Hein_2019_CVPR_Workshops,
author = {Hein, Matthias and Andriushchenko, Maksym and Bitterwolf, Julian},
title = {Why ReLU networks yield high-confidence predictions far away from the training data and how to mitigate the problem},
booktitle = {Proceedings of the IEEE/CVF Conference on Computer Vision and Pattern Recognition (CVPR) Workshops},
month = {June},
year = {2019}
}
Uncertainty-Guided Continual Learning in Bayesian Neural Networks - Extended Abstract-
[pdf]
[bibtex]@InProceedings{Ebrahimi_2019_CVPR_Workshops,
author = {Ebrahimi, Sayna and Elhoseiny, Mohamed and Darrell, Trevor and Rohrbach, Marcus},
title = {Uncertainty-Guided Continual Learning in Bayesian Neural Networks - Extended Abstract},
booktitle = {Proceedings of the IEEE/CVF Conference on Computer Vision and Pattern Recognition (CVPR) Workshops},
month = {June},
year = {2019}
}
Iterative Self-Learning: Semi-Supervised Improvement to Dataset Volumes and Model Accuracy-
[pdf]
[bibtex]@InProceedings{Dupre_2019_CVPR_Workshops,
author = {Dupre, Robert and Fajtl, Jiri and Argyriou, Vasileios and Remagnino, Paolo},
title = {Iterative Self-Learning: Semi-Supervised Improvement to Dataset Volumes and Model Accuracy},
booktitle = {Proceedings of the IEEE/CVF Conference on Computer Vision and Pattern Recognition (CVPR) Workshops},
month = {June},
year = {2019}
}
Deep Probabilistic Regression of Elements of SO(3) using Quaternion Averaging and Uncertainty Injection-
[pdf]
[bibtex]@InProceedings{Peretroukhin_2019_CVPR_Workshops,
author = {Peretroukhin, Valentin and Wagstaff, Brandon and Jonathan Kelly, and},
title = {Deep Probabilistic Regression of Elements of SO(3) using Quaternion Averaging and Uncertainty Injection},
booktitle = {Proceedings of the IEEE/CVF Conference on Computer Vision and Pattern Recognition (CVPR) Workshops},
month = {June},
year = {2019}
}
Improving Deep Network Robustness to Unknown Inputs with Objectosphere-
[pdf]
[bibtex]@InProceedings{Dhamija_2019_CVPR_Workshops,
author = {Raj Dhamija, Akshay and Gunther, Manuel and Boult, Terrance E.},
title = {Improving Deep Network Robustness to Unknown Inputs with Objectosphere},
booktitle = {Proceedings of the IEEE/CVF Conference on Computer Vision and Pattern Recognition (CVPR) Workshops},
month = {June},
year = {2019}
}
Learning Conditional Error Model for Simulated Time-Series Data-
[pdf]
[bibtex]@InProceedings{Shrivastava_2019_CVPR_Workshops,
author = {Shrivastava, Ashish and Tuzel, Oncel},
title = {Learning Conditional Error Model for Simulated Time-Series Data},
booktitle = {Proceedings of the IEEE/CVF Conference on Computer Vision and Pattern Recognition (CVPR) Workshops},
month = {June},
year = {2019}
}
SANE: Exploring Adversarial Robustness With Stochastically Activated Network Ensembles-
[pdf]
[bibtex]@InProceedings{Daya_2019_CVPR_Workshops,
author = {Ben Daya, Ibrahim and Javad Shafiee, Mohammad and Karg, Michelle and Scharfenberger, Christian and Wong, Alexander},
title = {SANE: Exploring Adversarial Robustness With Stochastically Activated Network Ensembles},
booktitle = {Proceedings of the IEEE/CVF Conference on Computer Vision and Pattern Recognition (CVPR) Workshops},
month = {June},
year = {2019}
}
Unsupervised Domain Adaptation via Calibrating Uncertainties-
[pdf]
[bibtex]@InProceedings{Han_2019_CVPR_Workshops,
author = {Han, Ligong and Zou, Yang and Gao, Ruijiang and Wang, Lezi and Metaxas, Dimitris},
title = {Unsupervised Domain Adaptation via Calibrating Uncertainties},
booktitle = {Proceedings of the IEEE/CVF Conference on Computer Vision and Pattern Recognition (CVPR) Workshops},
month = {June},
year = {2019}
}
Uncertainty aware audiovisual activity recognition using deep Bayesian variational inference-
[pdf]
[bibtex]@InProceedings{Subedar_2019_CVPR_Workshops,
author = {Subedar, Mahesh and Krishnan, Ranganath and Lopez Meyer, Paulo and Tickoo, Omesh and Huang, Jonathan},
title = {Uncertainty aware audiovisual activity recognition using deep Bayesian variational inference},
booktitle = {Proceedings of the IEEE/CVF Conference on Computer Vision and Pattern Recognition (CVPR) Workshops},
month = {June},
year = {2019}
}
GAN Data Augmentation Through Active Learning Inspired Sample Acquisition-
[pdf]
[bibtex]@InProceedings{Nielsen_2019_CVPR_Workshops,
author = {Nielsen, Christopher and Okoniewski, Michal},
title = {GAN Data Augmentation Through Active Learning Inspired Sample Acquisition},
booktitle = {Proceedings of the IEEE/CVF Conference on Computer Vision and Pattern Recognition (CVPR) Workshops},
month = {June},
year = {2019}
}