PoseNet2：Geometric loss functions for camera pose regression with deep learning 论文笔记

时间 2020-12-30

标签语义 SLAM 繁體版

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PoseNet2：Geometric loss functions for camera pose regression with deep learning 剑桥大学 2017.5 相机重定位，indoor, outdoor，RGB，RGBD 个人总结：这篇论文是posenet 的损失函数改进版本，但是性能得到了非常大的提升。论文很多细节都讲得非常好，非常详细清晰的说明了为何要选择这种函数/表

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1. Introduction to Camera Pose Estimation with Deep Learning && 2019 论文笔记
2. 【论文笔记】PoseGAN: A Pose-to-Image Translation Framework for Camera Localization
3. ECCV 2018 DSLT:《Deep Regression Tracking with Shrinkage Loss》论文笔记
4. Wide & Deep Learning for Recommender Systems论文笔记
5. Learning to Track at 100 FPS with Deep Regression Networks 论文笔记
6. 【论文笔记】Learning Multi-view Camera Relocalization with Graph Neural Networks（CVPR2020）
7. 每天一篇论文 381/1000 3D Scene Geometry-Aware Constraint for Camera Localization with Deep Learning
8. 论文笔记：Understanding the Limitations of CNN-based Absolute Camera Pose Regression
9. Understanding the Limitations of CNN-based Absolute Camera Pose Regression 2019 论文笔记
10. 论文笔记：《Playing Atari with Deep Reinforcement Learning》

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