論文筆記：Reinforcing LiDAR-Based 3D Object Detection with RGB and 3D Information
論文筆記：Reinforcing LiDAR-Based 3D Object Detection with RGB and 3D Information 簡介 本文提出了一個融合了RGB-D和3D點雲信息的3-D目標檢測方法。融合了RGB-D的方法在速度有所下降的情況下準確率得到了一定的提高。 方法 這是一個三階段方法。 第一階段，用PointRCNN的第一階段提取點雲的3D Proposal 第
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相關文章
- 1. CVPR2018_Frustum PointNets for 3D Object Detection from RGB-D Data
- 2. 論文閱讀速記：PointRCNN：3D Object Proposal Generation and Detection from Point Cloud
- 3. Deep Hough Voting for 3D Object Detection in Point Clouds 論文筆記
- 4. BirdNet: a 3D Object Detection Framework from LiDAR information
- 5. 《論文閱讀》ImVoteNet: Boosting 3D Object Detection in Point Clouds with Image Votes
- 6. 論文筆記：Integrated Object Detection and Tracking with Tracklet-Conditioned Detection
- 7. 綜述：3D目標檢測於RGB-D（Object detection in RGB-D images）
- 8. 【論文閱讀】【3D目標檢測】BirdNet: a 3D Object Detection Framework from LiDAR Information
- 9. 3D Object Detection 3D目標檢測綜述
- 10. Joint 3D Proposal Generation and Object Detection from View Aggregation論文學習