[論文解讀]SuperGlue: Learning Feature Matching with Graph Neural Networks
SuperGlue: Learning Feature Matching with Graph Neural Networks 個人感受： 這個是繼SuperPoint 後該組又一次推進，感覺效果更加強了，如果superpoint只是在嘗試學習傳統方法的流程，LFNet end-to-end training就在benchmark上超越了SIFT，近來CVPR19的D2Net 就直接跳出了傳統方法
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相關文章
- 1. SuperGlue: Learning Feature Matching with Graph Neural Networks 2019 論文筆記
- 2. Few-Shot Learning with Graph Neural Networks
- 3. 論文閱讀筆記《Few-Shot Learning with Graph Neural Networks》
- 4. Few-shot Learning with Graph Neural Networks
- 5. node2vec: Scalable Feature Learning for Networks論文解讀
- 6. Matching Networks for One Shot Learning論文解讀
- 7. 【論文筆記】Learning Multi-view Camera Relocalization with Graph Neural Networks（CVPR2020）
- 8. 論文《Matching Networks for One Shot Learning》閱讀
- 9. 《Deep Learning of Graph Matching》論文閱讀
- 10. FEW-SHOT LEARNING WITH GRAPH NEURAL NETWORKS翻譯