相关参考文献
注意：仅列出部分参考文献，下载原文获取全部文献信息。Efficient semantic segmentation with pyramidal fusion
Marin Orsic et al.
PATTERN RECOGNITION (2021)
Deep High-Resolution Representation Learning for Visual Recognition
Jingdong Wang et al.
IEEE TRANSACTIONS ON PATTERN ANALYSIS AND MACHINE INTELLIGENCE (2021)
OCNet: Object Context for Semantic Segmentation
Yuhui Yuan et al.
INTERNATIONAL JOURNAL OF COMPUTER VISION (2021)
Semantic Understanding of Scenes Through the ADE20K Dataset
Bolei Zhou et al.
INTERNATIONAL JOURNAL OF COMPUTER VISION (2019)
ERFNet: Efficient Residual Factorized ConvNet for Real-Time Semantic Segmentation
Eduardo Romera et al.
IEEE TRANSACTIONS ON INTELLIGENT TRANSPORTATION SYSTEMS (2018)
DeepLab: Semantic Image Segmentation with Deep Convolutional Nets, Atrous Convolution, and Fully Connected CRFs
Liang-Chieh Chen et al.
IEEE TRANSACTIONS ON PATTERN ANALYSIS AND MACHINE INTELLIGENCE (2018)
Dense Decoder Shortcut Connections for Single-Pass Semantic Segmentation
Piotr Bilinski et al.
2018 IEEE/CVF CONFERENCE ON COMPUTER VISION AND PATTERN RECOGNITION (CVPR) (2018)
SegNet: A Deep Convolutional Encoder-Decoder Architecture for Image Segmentation
Vijay Badrinarayanan et al.
IEEE TRANSACTIONS ON PATTERN ANALYSIS AND MACHINE INTELLIGENCE (2017)
Fully Convolutional Networks for Semantic Segmentation
Evan Shelhamer et al.
IEEE TRANSACTIONS ON PATTERN ANALYSIS AND MACHINE INTELLIGENCE (2017)
Densely Connected Convolutional Networks
Gao Huang et al.
30TH IEEE CONFERENCE ON COMPUTER VISION AND PATTERN RECOGNITION (CVPR 2017) (2017)
Xception: Deep Learning with Depthwise Separable Convolutions
Francois Chollet
30TH IEEE CONFERENCE ON COMPUTER VISION AND PATTERN RECOGNITION (CVPR 2017) (2017)
Laplacian Pyramid Reconstruction and Refinement for Semantic Segmentation
Golnaz Ghiasi et al.
COMPUTER VISION - ECCV 2016, PT III (2016)
SLIC Superpixels Compared to State-of-the-Art Superpixel Methods
Radhakrishna Achanta et al.
IEEE TRANSACTIONS ON PATTERN ANALYSIS AND MACHINE INTELLIGENCE (2012)
GrabCut - Interactive foreground extraction using iterated graph cuts
C Rother et al.
ACM TRANSACTIONS ON GRAPHICS (2004)
分享论文
