RobustNet: Improving Domain Generalization in Urban-Scene Segmentation via Instance Selective Whitening
暂无分享,去创建一个
Seungryong Kim | Jaegul Choo | Sungha Choi | Sanghun Jung | Huiwon Yun | Joanne Kim | J. Kim | J. Choo | Seungryong Kim | Sanghun Jung | Huiwon Yun | Sungha Choi | Huiwon Yun
[1] Luc Van Gool,et al. ROAD: Reality Oriented Adaptation for Semantic Segmentation of Urban Scenes , 2017, 2018 IEEE/CVF Conference on Computer Vision and Pattern Recognition.
[2] Larry S. Davis,et al. DCAN: Dual Channel-wise Alignment Networks for Unsupervised Scene Adaptation , 2018, ECCV.
[3] Leon A. Gatys,et al. Texture Synthesis Using Convolutional Neural Networks , 2015, NIPS.
[4] Tatsuya Harada,et al. Maximum Classifier Discrepancy for Unsupervised Domain Adaptation , 2017, 2018 IEEE/CVF Conference on Computer Vision and Pattern Recognition.
[5] Xiaogang Wang,et al. Pyramid Scene Parsing Network , 2016, 2017 IEEE Conference on Computer Vision and Pattern Recognition (CVPR).
[6] Kate Saenko,et al. Deep CORAL: Correlation Alignment for Deep Domain Adaptation , 2016, ECCV Workshops.
[7] Mengjie Zhang,et al. Domain Generalization for Object Recognition with Multi-task Autoencoders , 2015, 2015 IEEE International Conference on Computer Vision (ICCV).
[8] Patrick Pérez,et al. ADVENT: Adversarial Entropy Minimization for Domain Adaptation in Semantic Segmentation , 2018, 2019 IEEE/CVF Conference on Computer Vision and Pattern Recognition (CVPR).
[9] Ming-Hsuan Yang,et al. Learning to Adapt Structured Output Space for Semantic Segmentation , 2018, 2018 IEEE/CVF Conference on Computer Vision and Pattern Recognition.
[10] Luc Van Gool,et al. DLOW: Domain Flow for Adaptation and Generalization , 2018, 2019 IEEE/CVF Conference on Computer Vision and Pattern Recognition (CVPR).
[11] François Laviolette,et al. Domain-Adversarial Training of Neural Networks , 2015, J. Mach. Learn. Res..
[12] Yongxin Yang,et al. Episodic Training for Domain Generalization , 2019, 2019 IEEE/CVF International Conference on Computer Vision (ICCV).
[13] Wei Liu,et al. ParseNet: Looking Wider to See Better , 2015, ArXiv.
[14] David J. Kriegman,et al. Image to Image Translation for Domain Adaptation , 2017, 2018 IEEE/CVF Conference on Computer Vision and Pattern Recognition.
[15] Victor S. Lempitsky,et al. Unsupervised Domain Adaptation by Backpropagation , 2014, ICML.
[16] Wei Zhou,et al. Feature-Critic Networks for Heterogeneous Domain Generalization , 2019, ICML.
[17] Jian Sun,et al. Deep Residual Learning for Image Recognition , 2015, 2016 IEEE Conference on Computer Vision and Pattern Recognition (CVPR).
[18] Alberto L. Sangiovanni-Vincentelli,et al. Domain Randomization and Pyramid Consistency: Simulation-to-Real Generalization Without Accessing Target Domain Data , 2019, 2019 IEEE/CVF International Conference on Computer Vision (ICCV).
[19] Trevor Darrell,et al. Fully Convolutional Networks for Semantic Segmentation , 2017, IEEE Transactions on Pattern Analysis and Machine Intelligence.
[20] Maneesh Kumar Singh,et al. DRIT++: Diverse Image-to-Image Translation via Disentangled Representations , 2019, International Journal of Computer Vision.
[21] Swami Sankaranarayanan,et al. MetaReg: Towards Domain Generalization using Meta-Regularization , 2018, NeurIPS.
[22] Timothy M. Hospedales,et al. Learning to Generate Novel Domains for Domain Generalization , 2020, ECCV.
[23] Jaegul Choo,et al. Cars Can’t Fly Up in the Sky: Improving Urban-Scene Segmentation via Height-Driven Attention Networks , 2020, 2020 IEEE/CVF Conference on Computer Vision and Pattern Recognition (CVPR).
[24] Sridha Sridharan,et al. Correlation-aware Adversarial Domain Adaptation and Generalization , 2019, Pattern Recognit..
[25] Sergey Ioffe,et al. Batch Normalization: Accelerating Deep Network Training by Reducing Internal Covariate Shift , 2015, ICML.
[26] Vladlen Koltun,et al. Playing for Data: Ground Truth from Computer Games , 2016, ECCV.
[27] Trevor Darrell,et al. BDD100K: A Diverse Driving Video Database with Scalable Annotation Tooling , 2018, ArXiv.
[28] Shawn D. Newsam,et al. Improving Semantic Segmentation via Video Propagation and Label Relaxation , 2018, 2019 IEEE/CVF Conference on Computer Vision and Pattern Recognition (CVPR).
[29] Philip David,et al. Domain Adaptation for Semantic Segmentation of Urban Scenes , 2017 .
[30] Jan Kautz,et al. Multimodal Unsupervised Image-to-Image Translation , 2018, ECCV.
[31] Andrea Vedaldi,et al. Instance Normalization: The Missing Ingredient for Fast Stylization , 2016, ArXiv.
[32] Leon A. Gatys,et al. Image Style Transfer Using Convolutional Neural Networks , 2016, 2016 IEEE Conference on Computer Vision and Pattern Recognition (CVPR).
[33] Trevor Darrell,et al. FCNs in the Wild: Pixel-level Adversarial and Constraint-based Adaptation , 2016, ArXiv.
[34] Peter Kontschieder,et al. The Mapillary Vistas Dataset for Semantic Understanding of Street Scenes , 2017, 2017 IEEE International Conference on Computer Vision (ICCV).
[35] Bernhard Schölkopf,et al. Domain Generalization via Invariant Feature Representation , 2013, ICML.
[36] Ming-Hsuan Yang,et al. Universal Style Transfer via Feature Transforms , 2017, NIPS.
[37] Taesung Park,et al. CyCADA: Cycle-Consistent Adversarial Domain Adaptation , 2017, ICML.
[38] In So Kweon,et al. Unsupervised Intra-Domain Adaptation for Semantic Segmentation Through Self-Supervision , 2020, 2020 IEEE/CVF Conference on Computer Vision and Pattern Recognition (CVPR).
[39] Namil Kim,et al. Drop to Adapt: Learning Discriminative Features for Unsupervised Domain Adaptation , 2019, 2019 IEEE/CVF International Conference on Computer Vision (ICCV).
[40] George Papandreou,et al. Encoder-Decoder with Atrous Separable Convolution for Semantic Image Segmentation , 2018, ECCV.
[41] Donald A. Adjeroh,et al. Unified Deep Supervised Domain Adaptation and Generalization , 2017, 2017 IEEE International Conference on Computer Vision (ICCV).
[42] Antonio M. López,et al. The SYNTHIA Dataset: A Large Collection of Synthetic Images for Semantic Segmentation of Urban Scenes , 2016, 2016 IEEE Conference on Computer Vision and Pattern Recognition (CVPR).
[43] Koby Crammer,et al. Analysis of Representations for Domain Adaptation , 2006, NIPS.
[44] Daniel C. Castro,et al. Domain Generalization via Model-Agnostic Learning of Semantic Features , 2019, NeurIPS.
[45] Bohyung Han,et al. Learning to Optimize Domain Specific Normalization for Domain Generalization , 2019, ECCV.
[46] Daniel Rueckert,et al. Medical Image Computing and Computer-Assisted Intervention − MICCAI 2017: 20th International Conference, Quebec City, QC, Canada, September 11-13, 2017, Proceedings, Part II , 2017, Lecture Notes in Computer Science.
[47] D. Tao,et al. Deep Domain Generalization via Conditional Invariant Adversarial Networks , 2018, ECCV.
[48] Nicu Sebe,et al. Unsupervised Domain Adaptation Using Feature-Whitening and Consensus Loss , 2019, 2019 IEEE/CVF Conference on Computer Vision and Pattern Recognition (CVPR).
[49] Roberto Cipolla,et al. SegNet: A Deep Convolutional Encoder-Decoder Architecture for Image Segmentation , 2015, IEEE Transactions on Pattern Analysis and Machine Intelligence.
[50] Yongxin Yang,et al. Learning to Generalize: Meta-Learning for Domain Generalization , 2017, AAAI.
[51] Alex ChiChung Kot,et al. Domain Generalization with Adversarial Feature Learning , 2018, 2018 IEEE/CVF Conference on Computer Vision and Pattern Recognition.
[52] Lars Petersson,et al. Effective Use of Synthetic Data for Urban Scene Semantic Segmentation , 2018, ECCV.
[53] Xiangyu Zhang,et al. ShuffleNet V2: Practical Guidelines for Efficient CNN Architecture Design , 2018, ECCV.
[54] Sebastian Ramos,et al. The Cityscapes Dataset for Semantic Urban Scene Understanding , 2016, 2016 IEEE Conference on Computer Vision and Pattern Recognition (CVPR).
[55] Neha S. Wadia,et al. Whitening and second order optimization both destroy information about the dataset, and can make generalization impossible , 2020, ArXiv.
[56] Xiaoou Tang,et al. Two at Once: Enhancing Learning and Generalization Capacities via IBN-Net , 2018, ECCV.
[57] Mark Sandler,et al. MobileNetV2: Inverted Residuals and Linear Bottlenecks , 2018, 2018 IEEE/CVF Conference on Computer Vision and Pattern Recognition.
[58] Yang Zou,et al. Domain Adaptation for Semantic Segmentation via Class-Balanced Self-Training , 2018, ArXiv.
[59] Nicu Sebe,et al. Whitening and Coloring Batch Transform for GANs , 2018, ICLR.
[60] Luc Van Gool,et al. Exemplar Guided Unsupervised Image-to-Image Translation with Semantic Consistency , 2018, ICLR.
[61] Lei Huang,et al. Decorrelated Batch Normalization , 2018, 2018 IEEE/CVF Conference on Computer Vision and Pattern Recognition.
[62] Xueting Li,et al. A Closed-form Solution to Photorealistic Image Stylization , 2018, ECCV.
[63] Lei Huang,et al. Iterative Normalization: Beyond Standardization Towards Efficient Whitening , 2019, 2019 IEEE/CVF Conference on Computer Vision and Pattern Recognition (CVPR).
[64] George Papandreou,et al. Rethinking Atrous Convolution for Semantic Image Segmentation , 2017, ArXiv.
[65] Chi-Wing Fu,et al. Depth-Attentional Features for Single-Image Rain Removal , 2019, 2019 IEEE/CVF Conference on Computer Vision and Pattern Recognition (CVPR).
[66] Ping Luo,et al. Learning Deep Architectures via Generalized Whitened Neural Networks , 2017, ICML.
[67] Xiaoou Tang,et al. Switchable Whitening for Deep Representation Learning , 2019, 2019 IEEE/CVF International Conference on Computer Vision (ICCV).
[68] Jaegul Choo,et al. Image-To-Image Translation via Group-Wise Deep Whitening-And-Coloring Transformation , 2018, 2019 IEEE/CVF Conference on Computer Vision and Pattern Recognition (CVPR).