论文笔记01——PoseCNN：A Convolutional Neural Network for 6D Object Pose Estimation in Cluttered Scenes
参考链接： https://blog.csdn.net/nwu_NBL/article/details/83176353 论文标题：《PoseCNN：杂乱场景中物体6D姿态估计的卷积神经网络》 Abstract 机器人与现实世界进行交互时，对已知目标的6D姿态估计至关重要。由于对象的多样性，以及由于对象之间的杂波和遮挡而导致场景的复杂性，使得该问题具有挑战性。 本文介绍了一种用于6
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相关文章
- 1. PoseCNN: A Convolutional Neural Network for 6D Object Pose Estimation in Cluttered Scenes—2017（笔记）
- 2. Learning latent geometric consistency for 6D object pose estimation in heavily cluttered scenes
- 3. Segmentation-driven 6D Object Pose Estimation论文理解
- 4. 深度学习6D姿态估计pose estimation分类
- 5. 论文笔记：Convolutional Neural Network for Sentence Classification
- 6. 【论文笔记】PVNet: Pixel-wise Voting Network for 6DoF Pose Estimation
- 7. [CVPR 2019]Normalized Object Coordinate Space for Category-Level 6D Object Pose and Size Estimation
- 8. 【论文阅读】Semi-Dynamic Hypergraph Neural Network for 3D Pose Estimation，IJCAI-20
- 9. LiteFlowNet: A Lightweight Convolutional Neural Network for Optical Flow Estimation
- 10. 论文笔记：Cascaded Pyramid Network for Multi-Person Pose Estimation（CPN）