論文閱讀:High-Precision Depth Estimation Using Uncalibrated LiDAR and Stereo Fusion
論文閱讀:High-Precision Depth Estimation Using Uncalibrated LiDAR and Stereo Fusion 本文提出了一個用於未校準的LiDAR和雙目融合的用於深度估計的方法，本文的網絡由三部分組成： 校準模塊、融合模塊和優化模塊 摘要： 我們解決了從未校準的LiDAR點雲和立體圖像進行3D重建的問題。由於單獨使用每個傳感器進行三維重建在密度和精
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相關文章
- 1. 論文閱讀筆記《Learning monocular depth estimation infusing traditional stereo knowledge》
- 2. Anytime Stereo Image Depth Estimation on Mobile Devices論文閱讀筆記
- 3. 【論文閱讀】3D-CVF: Generating Joint Camera and LiDAR Features Using Cross-View Spatial Feature Fusion for
- 4. Pseudo-LiDAR from Visual Depth Estimation
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- 6. LIDAR and Monocular Camera Fusion: On-road Depth Completion for Autonomous Driving 論文筆記
- 7. 文章閱讀 - MVSNet: Depth Inference for Unstructured Multi-view Stereo (ECCV 2018)
- 8. 【論文筆記】LiDAR and Camera Calibration using Motion Estimated by Sensor Fusion Odometry
- 9. 論文閱讀：CVPR2016 Paper list
- 10. 【文獻閱讀】Sensor Fusion Algorithm Design in Detecting Vehicles Using Laser Scanner and Stereo Vision