LIDAR and Monocular Camera Fusion: On-road Depth Completion for Autonomous Driving 论文笔记
这是一篇通过lidar和单目相机进行深度补全的。由于深度相机只能捕获几米范围内的物体深度，因此深度相机很难感应到大规模的路况，距离、透明度、明亮的表面是RGBD相机的主要限制因素。 本文贡献 1.使用早期融合技术和resnet-50作为特征编码器。 2.A Residual Up-Projection block (RUB)修复空间分辨率。 3.上下文信息通过skip connections从编码
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相关文章
- 1. Self-Supervised Sparse-to-Dense:Self-Supervised Depth Completion from LiDAR and Monocular Camera
- 2. 论文笔记_CV_AD_Visual Perception for Autonomous Driving
- 3. 【论文笔记】LiDAR and Camera Calibration using Motion Estimated by Sensor Fusion Odometry
- 4. 每天一篇论文 373/1000 PSEUDO-LIDAR++:ACCURATE DEPTH FOR 3D OBJECT DETECTION IN AUTONOMOUS DRIVING
- 5. Pseudo-LiDAR++: Accurate Depth for 3D Object Detection in Autonomous Driving Yurong
- 6. 论文阅读:High-Precision Depth Estimation Using Uncalibrated LiDAR and Stereo Fusion
- 7. 论文笔记：MultiNet: Real-time Joint Semantic Reasoning for Autonomous Driving
- 8. 【论文阅读】3D-CVF: Generating Joint Camera and LiDAR Features Using Cross-View Spatial Feature Fusion for
- 9. 论文阅读CVPR2019——Stereo R-CNN based 3D Object Detection for Autonomous Driving
- 10. 点云论文汇总