Guest Editorial: Special Issue on “Computer Vision for All Seasons: Adverse Weather and Lighting Conditions”

[1]  Luc Van Gool,et al.  Map-Guided Curriculum Domain Adaptation and Uncertainty-Aware Evaluation for Semantic Nighttime Image Segmentation , 2020, IEEE Transactions on Pattern Analysis and Machine Intelligence.

[2]  J. Zico Kolter,et al.  Learning perturbation sets for robust machine learning , 2020, ICLR.

[3]  D. Cremers,et al.  4Seasons: A Cross-Season Dataset for Multi-Weather SLAM in Autonomous Driving , 2020, GCPR.

[4]  Jianbo Shi,et al.  ForkGAN: Seeing into the Rainy Night , 2020, ECCV.

[5]  Robby T. Tan,et al.  All in One Bad Weather Removal Using Architectural Search , 2020, 2020 IEEE/CVF Conference on Computer Vision and Pattern Recognition (CVPR).

[6]  Matthias Bethge,et al.  A Simple Way to Make Neural Networks Robust Against Diverse Image Corruptions , 2020, ECCV.

[7]  Carsten Rother,et al.  Benchmarking the Robustness of Semantic Segmentation Models with Respect to Common Corruptions , 2019, International Journal of Computer Vision.

[8]  Raoul de Charette,et al.  Physics-Based Rendering for Improving Robustness to Rain , 2019, 2019 IEEE/CVF International Conference on Computer Vision (ICCV).

[9]  Torsten Sattler,et al.  A Cross-Season Correspondence Dataset for Robust Semantic Segmentation , 2019, 2019 IEEE/CVF Conference on Computer Vision and Pattern Recognition (CVPR).

[10]  Luc Van Gool,et al.  Guided Curriculum Model Adaptation and Uncertainty-Aware Evaluation for Semantic Nighttime Image Segmentation , 2019, 2019 IEEE/CVF International Conference on Computer Vision (ICCV).

[11]  Dengxin Dai,et al.  Curriculum Model Adaptation with Synthetic and Real Data for Semantic Foggy Scene Understanding , 2019, International Journal of Computer Vision.

[12]  Thomas G. Dietterich,et al.  Benchmarking Neural Network Robustness to Common Corruptions and Perturbations , 2018, ICLR.

[13]  Loong Fah Cheong,et al.  Robust Optical Flow in Rainy Scenes , 2018, ECCV.

[14]  Song Wang,et al.  Does Haze Removal Help CNN-Based Image Classification? , 2018, ECCV.

[15]  Jia Xu,et al.  Learning to See in the Dark , 2018, 2018 IEEE/CVF Conference on Computer Vision and Pattern Recognition.

[16]  Vishal M. Patel,et al.  Densely Connected Pyramid Dehazing Network , 2018, 2018 IEEE/CVF Conference on Computer Vision and Pattern Recognition.

[17]  Vishal M. Patel,et al.  Density-Aware Single Image De-raining Using a Multi-stream Dense Network , 2018, 2018 IEEE/CVF Conference on Computer Vision and Pattern Recognition.

[18]  Alex Bewley,et al.  Incremental Adversarial Domain Adaptation for Continually Changing Environments , 2017, 2018 IEEE International Conference on Robotics and Automation (ICRA).

[19]  Luc Van Gool,et al.  Semantic Foggy Scene Understanding with Synthetic Data , 2017, International Journal of Computer Vision.

[20]  Paul Newman,et al.  1 year, 1000 km: The Oxford RobotCar dataset , 2017, Int. J. Robotics Res..

[21]  Sebastian Ramos,et al.  The Cityscapes Dataset for Semantic Urban Scene Understanding , 2016, 2016 IEEE Conference on Computer Vision and Pattern Recognition (CVPR).

[22]  Michael S. Bernstein,et al.  ImageNet Large Scale Visual Recognition Challenge , 2014, International Journal of Computer Vision.

[23]  Pietro Perona,et al.  Microsoft COCO: Common Objects in Context , 2014, ECCV.

[24]  Andreas Geiger,et al.  Are we ready for autonomous driving? The KITTI vision benchmark suite , 2012, 2012 IEEE Conference on Computer Vision and Pattern Recognition.

[25]  Luc Van Gool,et al.  The Pascal Visual Object Classes (VOC) Challenge , 2010, International Journal of Computer Vision.

[26]  Dima Damen,et al.  Recognizing linked events: Searching the space of feasible explanations , 2009, 2009 IEEE Conference on Computer Vision and Pattern Recognition.

[27]  Robby T. Tan,et al.  Visibility in bad weather from a single image , 2008, 2008 IEEE Conference on Computer Vision and Pattern Recognition.

[28]  Shree K. Nayar,et al.  Vision and Rain , 2007, International Journal of Computer Vision.

[29]  Shree K. Nayar,et al.  Vision and the Atmosphere , 2002, International Journal of Computer Vision.