Seeing Objects in Dark with Continual Contrastive Learning

[1]  Chien-Yao Wang,et al.  You Only Learn One Representation: Unified Network for Multiple Tasks , 2021, J. Inf. Sci. Eng..

[2]  Chen Change Loy,et al.  Learning to Enhance Low-Light Image via Zero-Reference Deep Curve Estimation , 2021, IEEE Transactions on Pattern Analysis and Machine Intelligence.

[3]  H. Ko,et al.  Adverse Weather Image Translation with Asymmetric and Uncertainty-aware GAN , 2021, BMVC.

[4]  Luc Van Gool,et al.  ACDC: The Adverse Conditions Dataset with Correspondences for Semantic Driving Scene Understanding , 2021, 2021 IEEE/CVF International Conference on Computer Vision (ICCV).

[5]  Xiangyu Zhang,et al.  You Only Look One-level Feature , 2021, 2021 IEEE/CVF Conference on Computer Vision and Pattern Recognition (CVPR).

[6]  Fabio Pizzati,et al.  CoMoGAN: continuous model-guided image-to-image translation , 2021, 2021 IEEE/CVF Conference on Computer Vision and Pattern Recognition (CVPR).

[7]  Chien-Yao Wang,et al.  Scaled-YOLOv4: Scaling Cross Stage Partial Network , 2020, 2021 IEEE/CVF Conference on Computer Vision and Pattern Recognition (CVPR).

[8]  David Lopez-Paz,et al.  In Search of Lost Domain Generalization , 2020, ICLR.

[9]  Ding Liu,et al.  EnlightenGAN: Deep Light Enhancement Without Paired Supervision , 2019, IEEE Transactions on Image Processing.

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

[11]  Pierre H. Richemond,et al.  Bootstrap Your Own Latent: A New Approach to Self-Supervised Learning , 2020, NeurIPS.

[12]  Seungryong Kim,et al.  DUNIT: Detection-Based Unsupervised Image-to-Image Translation , 2020, 2020 IEEE/CVF Conference on Computer Vision and Pattern Recognition (CVPR).

[13]  Nicolas Usunier,et al.  End-to-End Object Detection with Transformers , 2020, ECCV.

[14]  Stefano Soatto,et al.  FDA: Fourier Domain Adaptation for Semantic Segmentation , 2020, 2020 IEEE/CVF Conference on Computer Vision and Pattern Recognition (CVPR).

[15]  Shang-Hong Lai,et al.  Multimodal Structure-Consistent Image-to-Image Translation , 2020, AAAI.

[16]  Dragomir Anguelov,et al.  Scalability in Perception for Autonomous Driving: Waymo Open Dataset , 2019, 2020 IEEE/CVF Conference on Computer Vision and Pattern Recognition (CVPR).

[17]  Qiang Xu,et al.  nuScenes: A Multimodal Dataset for Autonomous Driving , 2019, 2020 IEEE/CVF Conference on Computer Vision and Pattern Recognition (CVPR).

[18]  Trevor Darrell,et al.  BDD100K: A Diverse Driving Dataset for Heterogeneous Multitask Learning , 2018, 2020 IEEE/CVF Conference on Computer Vision and Pattern Recognition (CVPR).

[19]  Ross B. Girshick,et al.  Focal Loss for Dense Object Detection , 2017, IEEE Transactions on Pattern Analysis and Machine Intelligence.

[20]  Nicu Sebe,et al.  Cross-Domain Car Detection Using Unsupervised Image-to-Image Translation: From Day to Night , 2019, 2019 International Joint Conference on Neural Networks (IJCNN).

[21]  Xiaojie Guo,et al.  Kindling the Darkness: A Practical Low-light Image Enhancer , 2019, ACM Multimedia.

[22]  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).

[23]  Luc Van Gool,et al.  Night-to-Day Image Translation for Retrieval-based Localization , 2018, 2019 International Conference on Robotics and Automation (ICRA).

[24]  Michelle Karg,et al.  NightOwls: A Pedestrians at Night Dataset , 2018, ACCV.

[25]  Shang-Hong Lai,et al.  AugGAN: Cross Domain Adaptation with GAN-Based Data Augmentation , 2018, ECCV.

[26]  Jan Kautz,et al.  Multimodal Unsupervised Image-to-Image Translation , 2018, ECCV.

[27]  Jan Kautz,et al.  Unsupervised Image-to-Image Translation Networks , 2017, NIPS.

[28]  Harri Valpola,et al.  Weight-averaged consistency targets improve semi-supervised deep learning results , 2017, ArXiv.

[29]  Razvan Pascanu,et al.  Overcoming catastrophic forgetting in neural networks , 2016, Proceedings of the National Academy of Sciences.

[30]  François Laviolette,et al.  Domain-Adversarial Training of Neural Networks , 2015, J. Mach. Learn. Res..

[31]  Namil Kim,et al.  Multispectral pedestrian detection: Benchmark dataset and baseline , 2015, 2015 IEEE Conference on Computer Vision and Pattern Recognition (CVPR).

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

[33]  Gordon Wyeth,et al.  SeqSLAM: Visual route-based navigation for sunny summer days and stormy winter nights , 2012, 2012 IEEE International Conference on Robotics and Automation.

[34]  Pietro Perona,et al.  Pedestrian Detection: An Evaluation of the State of the Art , 2012, IEEE Transactions on Pattern Analysis and Machine Intelligence.