Collection and research of dataset for SLAM
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[1] Tanke J, Kwon O H, Stotko P, et al. Bonn Activity Maps: Dataset Description[J]. .PDF. arXiv preprint arXiv:1912.06354, 2019.
- 包含人体跟踪、姿态和环境语义三维重建的数据集
- 波恩大学，项目、数据集主页
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[2] Wang S, Yue J, Dong Y, et al. A synthetic dataset for Visual SLAM evaluation[J]. Robotics and Autonomous Systems, 2019: 103336.
- 用于视觉 SLAM 评估的合成数据集
- 同济大学，期刊中科院三区， JCR Q2， IF 2.809
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[3] Kirsanov P, Gaskarov A, Konokhov F, et al. DISCOMAN: Dataset of Indoor SCenes for Odometry, Mapping And Navigation[J]. .PDF. arXiv preprint arXiv:1909.12146, 2019.
- DISCOMAN：用于里程计、制图和导航的室内场景数据集
- 三星 AI 中心，数据集随论文正式发表放出
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[4] Zheng J, Zhang J, Li J, et al. Structured3D: A Large Photo-realistic Dataset for Structured 3D Modeling[J]. .PDF. arXiv preprint arXiv:1908.00222, 2019.
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[5] Saran V, Lin J, Zakhor A. Augmented Annotations: Indoor Dataset Generation with Augmented Reality[J]. ISPRS-International Archives of the Photogrammetry, Remote Sensing and Spatial Information Sciences, 2019, 4213: 873-879.
- 增强注释：具有增强现实的室内数据集生成
- 加州大学伯克利分校 项目主页
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[6] Saeedi S, Carvalho E, Li W, et al. Characterizing Visual Localization and Mapping Datasets[C]//2019 IEEE International Conference on Robotics and Automation (ICRA). 2019.
- 描述可视化定位于建图的数据集
- 帝国理工学院计算机系 数据集地址
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[7] Shan Z, Li R, Schwertfeger S. RGBD-Inertial Trajectory Estimation and Mapping for Ground Robots[J]. Sensors, 2019, 19(10): 2251.
- 用于地面机器人的 RGBD-惯导轨迹估计与建图
- 上海科技大学 Google Scholor
- 代码开源 演示视频 期刊：开源，中科院三区，JCR Q2Q3
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[8] Scheerlinck C, Rebecq H, Stoffregen T, et al. CED: Color event camera dataset[J]. arXiv preprint arXiv:1904.10772, CVPRW 2019.
- 彩色事件相机
- 苏黎世大学 项目主页 Google Scholor
- 基于事件的视觉研究：Event-based Vision: A Survey. CVPR 2019
- Focus is all you need: Loss functions for event-based vision. 2019
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[9] Wenzel P, Wang R, Yang N, et al. 4Seasons: A Cross-Season Dataset for Multi-Weather SLAM in Autonomous Driving[J]. arXiv preprint arXiv:2009.06364, 2020.
- 4Seasons：自动驾驶中多天气SLAM的跨季节数据集
- 慕尼黑工业大学 Nan Yang
- 数据集网页：http://www.4seasons-dataset.com/
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[10] Zuñiga-Noël D, Jaenal A, Gomez-Ojeda R, et al. The UMA-VI dataset: Visual–inertial odometry in low-textured and dynamic illumination environments[J]. The International Journal of Robotics Research, 2020: 0278364920938439.
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[11] Wang W, Zhu D, Wang X, et al. TartanAir: A Dataset to Push the Limits of Visual SLAM[J]. arXiv preprint arXiv:2003.14338, 2020.
- TartanAir：突破视觉 SLAM 极限的数据集
- CMU，港中文；数据集公开：http://theairlab.org/tartanair-dataset/
- 朱德龙师兄参与的一项工作，上个月推荐过了，这个月刚完善网站再推荐一遍，并在 CVPR 2020 组织了 workshop
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[12] Jinjin Gu, Haoming Cai, Haoyu Chen, Xiaoxing Ye, et al. PIPAL: a Large-Scale Image Quality Assessment Dataset for Perceptual Image Restoration[J]. arXiv preprint arXiv:2007.12142, 2020.
- PIPAL：用于感知图像恢复的大规模图像质量评估数据集
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[13] Quang-Hieu Pham, Pierre Sevestre, et al. A*3D Dataset: Towards Autonomous Driving in Challenging Environments[J]. .PDF. arXiv preprint arXiv:1909.07541, 2019.
- A * 3D数据集：在充满挑战的环境中实现自动驾驶
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[14] Wang, Wenshan and Zhu, Delong and Wang, Xiangwei and Hu, et al. TartanAir: A Dataset to Push the Limits of Visual SLAM[J]. .PDF. arXiv preprint arXiv:2003.14338, 2020.
- TartanAir：突破Visual SLAM极限的数据集 数据集地址
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[15] Adam Ligocki, Ales Jelinek, Ludek Zalud. Brno Urban Dataset -- The New Data for Self-Driving Agents and Mapping Tasks[J]. .PDF. arXiv preprint arXiv:1909.06897, 2019.
- 布尔诺城市数据集-自驾车代理和制图任务的新数据 数据集地址
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[16] Zhu, Zunjie and Xu, Feng and Yan. Real-time Indoor Scene Reconstruction with RGBD and Inertial Input[J]. .PDF. ICME’2019, 2019.
- FMDataset旨在验证Dense-SLAM系统在传感器运动的不同速度下的鲁棒性 数据集地址
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RobotCar 数据集：https://robotcar-dataset.robots.ox.ac.uk/