论文笔记：MultiNet: Real-time Joint Semantic Reasoning for Autonomous Driving
曾经Kitti道路分割排名第一的方案， 现为Kitti上UM-road 排名35的方案。 main contribution： 1.将分类、检测、分割三个任务结合起来，共用encoder框架。 2.简单，效果还好。 3.效率高，23 fps （没说在什么环境下）架构 architecture：框架 共享一个encoder，对不一样的任务设计不一样的decoder性能 encoder: 用于提取特征
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相关文章
- 1. MultiNet: Real-time Joint Semantic Reasoning for AutonomousDriving
- 2. 论文笔记_CV_AD_Visual Perception for Autonomous Driving
- 3. LIDAR and Monocular Camera Fusion: On-road Depth Completion for Autonomous Driving 论文笔记
- 4. 论文笔记_2018-ECCV-Joint Task-Recursive Learning for Semantic Segmentation and Depth Estimation
- 5. Pillar-based Object Detection for Autonomous Driving
- 6. Stereo Vision-based Semantic 3D Object and Ego-motion Tracking for Autonomous Driving
- 7. [论文笔记] Enhancements of V2X Communication in Support of Cooperative Autonomous Driving
- 8. 论文阅读CVPR2019——Stereo R-CNN based 3D Object Detection for Autonomous Driving
- 9. 【论文阅读】A survey of deep learning techniques for autonomous driving
- 10. [论文解读]Multi-View 3D Object Detection Network for Autonomous Driving