GRNet: Learning Multi-view Camera Relocalization with Graph Neural Networks CVPR 2020 论文笔记
驭势科技, 北京大学机器感知重点实验室, 北京长城航空测控技术研究所 本文提出了一种使用多视角图像进行相机重定位的图神经网络。 该网络可以使得不连续帧之间进行信息传递，相比于只能在相邻前后帧之间进行信息传递的 序列输入和LTSM，其能捕获更多视角信息以进行重定位。因此LSTM只是一种GNN的特殊情况。 为了让GNN能适应于重定位任务，作者重新设计了节点、边、嵌入函数，使用CNN和GNN分别用于特征
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相关文章
- 1. 【论文笔记】Learning Multi-view Camera Relocalization with Graph Neural Networks（CVPR2020）
- 2. Few-Shot Learning with Graph Neural Networks笔记
- 3. [2018][ICLR]FEW-SHOT LEARNING WITH GRAPH NEURAL NETWORKS 论文笔记
- 4. SuperGlue: Learning Feature Matching with Graph Neural Networks 2019 论文笔记
- 5. 论文阅读笔记《Few-Shot Learning with Graph Neural Networks》
- 6. FEW-SHOT LEARNING WITH GRAPH NEURAL NETWORKS 论文笔记
- 7. Few-shot Learning with Graph Neural Networks
- 8. Few-Shot Learning with Graph Neural Networks
- 9. 笔记《Graph Neural Tangent Kernel: Fusing Graph Neural Networks with Graph Kernels》-NeurIPS 2019
- 10. 论文笔记:Few-Shot Lear With Graph Neural Networks