CamNet: Coarse-to-Fine Retrieval for Camera Re-Localization 論文筆記
CamNet: Coarse-to-Fine Retrieval for Camera Re-Localization 商湯、香港大學、港中文，RGB相機重定位，2019.6 1.摘要 本文模型針對的是相機重定位任務，基於檢索的模型被認爲是比較有潛力的方向，因爲可以很容易的泛化到其他場景。作者觀察到現有方法的瓶頸在於檢索模塊：這些方法對檢索和相關姿勢迴歸任務都使用相同的特徵，這對學習有潛在的影響。
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相關文章
- 1. Camera Relocalization by Exploiting Multi-View Constraints for Scene Coordinates Regression 2019論文筆記
- 2. PoseNet: A Convolutional Network for Real-Time 6-DOF Camera Relocalization 2015論文筆記
- 3. 2017-ICCV-SVDNet for Pedestrian Retrieval 論文筆記
- 4. Backtracking Regression Forests for Accurate Camera Relocalization
- 5. 【論文筆記】Learning Multi-view Camera Relocalization with Graph Neural Networks（CVPR2020）
- 6. Relative Geometry-Aware Siamese Neural Networkfor 6DOF Camera Relocalization 2019 論文筆記
- 7. GRNet: Learning Multi-view Camera Relocalization with Graph Neural Networks CVPR 2020 論文筆記
- 8. PoseNet: A Convolutional Network for Real-Time 6-DOF Camera Relocalization論文閱讀
- 9. 論文翻譯CamNet: Coarse-to-Fine Retrieval forCamera Re-Localization
- 10. GN-Net: The Gauss-Newton Loss for Multi-Weather Relocalization 論文筆記 2019