【CVPR2018】ERFNet: Efficient Residual Factorized ConvNet for Real-time Semantic Segmentation
作者 摘要 语义分割网络可以端到端训练，并准确地在像素级对多种目标分类。本文提出一个可实时运行且结果准确的语义分割架构。本架构核心是一个新层，使用residual connections和factorized convolutions，得以保证准确和高效。在单卡Titan X可达83FPS，Jetson TX1(英伟达GPU开发板)可达7FPS。在公开数据集Cityscapes上准确率类似于s
相关文章
- 1. 论文阅读（详细）：ERFNet: Efficient Residual Factorized ConvNet for Real-Time Semantic Segmentation
- 2. 【图像分割论文阅读】Efficient ConvNet for Real-time Semantic Segmentation
- 3. Context Encoding for Semantic Segmentation[CVPR2018]
- 4. Learning to Adapt Structured Output Space for Semantic Segmentation——CVPR2018
- 5. 【CVPR2018】MobileFaceNets Efficient CNNs for Accurate RealTime Face Verification on Mobile Devices
- 6. Context Encoding for Semantic Segmentation
- 7. 语义分割--LinkNet: Exploiting Encoder Representations for Efficient Semantic Segmentation
- 8. 《Dense Residual Network for Retinal Vessel Segmentation》
- 9. 轻量级实时语义分割：ENet & ERFNet
- 10. FCN-Fully Convolutional Networks for Semantic Segmentation
- 更多相关文章...
- • Swift for 循环 - Swift 教程
- • Scala for循环 - Scala教程
- • Composer 安装与使用
- • PHP开发工具
相关标签/搜索
每日一句
-
每一个你不满意的现在，都有一个你没有努力的曾经。
最新文章
欢迎关注本站公众号,获取更多信息
相关文章
- 1. 论文阅读（详细）：ERFNet: Efficient Residual Factorized ConvNet for Real-Time Semantic Segmentation
- 2. 【图像分割论文阅读】Efficient ConvNet for Real-time Semantic Segmentation
- 3. Context Encoding for Semantic Segmentation[CVPR2018]
- 4. Learning to Adapt Structured Output Space for Semantic Segmentation——CVPR2018
- 5. 【CVPR2018】MobileFaceNets Efficient CNNs for Accurate RealTime Face Verification on Mobile Devices
- 6. Context Encoding for Semantic Segmentation
- 7. 语义分割--LinkNet: Exploiting Encoder Representations for Efficient Semantic Segmentation
- 8. 《Dense Residual Network for Retinal Vessel Segmentation》
- 9. 轻量级实时语义分割：ENet & ERFNet
- 10. FCN-Fully Convolutional Networks for Semantic Segmentation