语义分割--Efficient and Robust Deep Networks for Semantic Segmentation
Efficient and Robust Deep Networks for Semantic Segmentation Code: https://lmb.informatik.uni-freiburg.de/Publications/2017/OB17a/ 在 Up-Convolutional Networks 的基础上，提出了 Part-Net，Fast-Net，M-Net。 三个网络的侧重
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相关文章
- 1. 语义分割--Global Deconvolutional Networks for Semantic Segmentation
- 2. 语义分割--Efficient Deep Models for Monocular Road Segmentation
- 3. 语义分割--Full-Resolution Residual Networks for Semantic Segmentation in Street Scenes
- 4. 语义分割--Understanding Convolution for Semantic Segmentation
- 5. 语义分割--LinkNet: Exploiting Encoder Representations for Efficient Semantic Segmentation
- 6. 语义分割--Deep Dual Learning for Semantic Image Segmentation
- 7. 语义分割--Fully Convolutional DenseNets for Semantic Segmentation
- 8. 语义分割，ICNet for Real-Time Semantic Segmentation
- 9. 语义分割--RefineNet: Multi-Path Refinement Networks for High-Resolution Semantic Segmentation
- 10. Squeeze-and-Attention Networks for Semantic Segmentation | CVPR2020