BiSeNet: Bilateral Segmentation Network for Real-time Semantic Segmentation
暂无分享,去创建一个
Gang Yu | Changxin Gao | Nong Sang | Chao Peng | Jingbo Wang | Changqian Yu | Chao Peng | Gang Yu | Changxin Gao | N. Sang | Jingbo Wang | Changqian Yu
[1] Yi Yang,et al. Attention to Scale: Scale-Aware Semantic Image Segmentation , 2015, 2016 IEEE Conference on Computer Vision and Pattern Recognition (CVPR).
[2] Forrest N. Iandola,et al. SqueezeNet: AlexNet-level accuracy with 50x fewer parameters and <1MB model size , 2016, ArXiv.
[3] Sepp Hochreiter,et al. Speeding up Semantic Segmentation for Autonomous Driving , 2016 .
[4] Roberto Cipolla,et al. SegNet: A Deep Convolutional Encoder-Decoder Architecture for Image Segmentation , 2015, IEEE Transactions on Pattern Analysis and Machine Intelligence.
[5] Xiaojuan Qi,et al. ICNet for Real-Time Semantic Segmentation on High-Resolution Images , 2017, ECCV.
[6] Trevor Darrell,et al. Fully Convolutional Networks for Semantic Segmentation , 2017, IEEE Transactions on Pattern Analysis and Machine Intelligence.
[7] Michael S. Bernstein,et al. ImageNet Large Scale Visual Recognition Challenge , 2014, International Journal of Computer Vision.
[8] Sergey Ioffe,et al. Batch Normalization: Accelerating Deep Network Training by Reducing Internal Covariate Shift , 2015, ICML.
[9] Garrison W. Cottrell,et al. Understanding Convolution for Semantic Segmentation , 2017, 2018 IEEE Winter Conference on Applications of Computer Vision (WACV).
[10] Guosheng Lin,et al. Efficient Piecewise Training of Deep Structured Models for Semantic Segmentation , 2015, 2016 IEEE Conference on Computer Vision and Pattern Recognition (CVPR).
[11] Xiaoxiao Li,et al. Not All Pixels Are Equal: Difficulty-Aware Semantic Segmentation via Deep Layer Cascade , 2017, 2017 IEEE Conference on Computer Vision and Pattern Recognition (CVPR).
[12] Ian D. Reid,et al. RefineNet : MultiPath Refinement Networks with Identity Mappings for High-Resolution Semantic Segmentation , 2016 .
[13] Enhua Wu,et al. Squeeze-and-Excitation Networks , 2017, IEEE Transactions on Pattern Analysis and Machine Intelligence.
[14] George Papandreou,et al. Rethinking Atrous Convolution for Semantic Image Segmentation , 2017, ArXiv.
[15] Iasonas Kokkinos,et al. DeepLab: Semantic Image Segmentation with Deep Convolutional Nets, Atrous Convolution, and Fully Connected CRFs , 2016, IEEE Transactions on Pattern Analysis and Machine Intelligence.
[16] Seunghoon Hong,et al. Learning Deconvolution Network for Semantic Segmentation , 2015, 2015 IEEE International Conference on Computer Vision (ICCV).
[17] Alex Graves,et al. Recurrent Models of Visual Attention , 2014, NIPS.
[18] Andrew Zisserman,et al. Very Deep Convolutional Networks for Large-Scale Image Recognition , 2014, ICLR.
[19] Xiaogang Wang,et al. Residual Attention Network for Image Classification , 2017, 2017 IEEE Conference on Computer Vision and Pattern Recognition (CVPR).
[20] Wei Liu,et al. ParseNet: Looking Wider to See Better , 2015, ArXiv.
[21] Yoshua Bengio,et al. Deep Sparse Rectifier Neural Networks , 2011, AISTATS.
[22] Anton van den Hengel,et al. High-performance Semantic Segmentation Using Very Deep Fully Convolutional Networks , 2016, ArXiv.
[23] Thomas Brox,et al. U-Net: Convolutional Networks for Biomedical Image Segmentation , 2015, MICCAI.
[24] Anton van den Hengel,et al. Real-time Semantic Image Segmentation via Spatial Sparsity , 2017, ArXiv.
[25] Sheng Tang,et al. Scale-Adaptive Convolutions for Scene Parsing , 2017, 2017 IEEE International Conference on Computer Vision (ICCV).
[26] Pietro Perona,et al. Microsoft COCO: Common Objects in Context , 2014, ECCV.
[27] Ian D. Reid,et al. RefineNet: Multi-path Refinement Networks for High-Resolution Semantic Segmentation , 2016, 2017 IEEE Conference on Computer Vision and Pattern Recognition (CVPR).
[28] Eugenio Culurciello,et al. ENet: A Deep Neural Network Architecture for Real-Time Semantic Segmentation , 2016, ArXiv.
[29] Vittorio Ferrari,et al. COCO-Stuff: Thing and Stuff Classes in Context , 2016, 2018 IEEE/CVF Conference on Computer Vision and Pattern Recognition.
[30] François Chollet,et al. Xception: Deep Learning with Depthwise Separable Convolutions , 2016, 2017 IEEE Conference on Computer Vision and Pattern Recognition (CVPR).
[31] Roberto Cipolla,et al. Segmentation and Recognition Using Structure from Motion Point Clouds , 2008, ECCV.
[32] Xiaogang Wang,et al. Pyramid Scene Parsing Network , 2016, 2017 IEEE Conference on Computer Vision and Pattern Recognition (CVPR).
[33] Xiangyu Zhang,et al. Large Kernel Matters — Improve Semantic Segmentation by Global Convolutional Network , 2017, 2017 IEEE Conference on Computer Vision and Pattern Recognition (CVPR).
[34] Geoffrey E. Hinton,et al. ImageNet classification with deep convolutional neural networks , 2012, Commun. ACM.
[35] Iasonas Kokkinos,et al. Semantic Image Segmentation with Deep Convolutional Nets and Fully Connected CRFs , 2014, ICLR.
[36] Charless C. Fowlkes,et al. Laplacian Pyramid Reconstruction and Refinement for Semantic Segmentation , 2016, ECCV.
[37] Sebastian Ramos,et al. The Cityscapes Dataset for Semantic Urban Scene Understanding , 2016, 2016 IEEE Conference on Computer Vision and Pattern Recognition (CVPR).
[38] Jian Sun,et al. Deep Residual Learning for Image Recognition , 2015, 2016 IEEE Conference on Computer Vision and Pattern Recognition (CVPR).
[39] Vladlen Koltun,et al. Multi-Scale Context Aggregation by Dilated Convolutions , 2015, ICLR.
[40] Gang Yu,et al. Learning a Discriminative Feature Network for Semantic Segmentation , 2018, 2018 IEEE/CVF Conference on Computer Vision and Pattern Recognition.