【图像分割论文阅读】DenseASPP for Semantic Segmentation in Street Scenes
本文由谷歌DeepMotion团队发布，发表于CVPR2018. 论文地址：DenseASPP for Semantic Segmentation in Street Scenes 背景 在自动驾驶领域，语义图像分割是基本的街道场景理解任务，它要求给高分辨率图像分每一个像素点进行分类.由于自动驾驶领域中场景中的目标尺度变化非常大.要求对高层次的特征在多尺度上正确编码.ASPP在获得更大感受野的同时
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相关文章
- 1. Semantic Segmentation---DenseASPP for Semantic Segmentation in Street Scenes（论文解读十一）
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- 4. DenseASPP for Semantic Segmentation in Street Scenes阅读笔记
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- 6. 语义分割--Full-Resolution Residual Networks for Semantic Segmentation in Street Scenes
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- 9. Full-Resolution Residual Networks for Semantic Segmentation in Street Scenes（FRRN））
- 10. 【图像分割论文阅读】RefineNet: Multi-Path Refinement Networks for High-Resolution Semantic Segmentation