Bell Labs robot garage for DANCE: Domain Adaptation of Networks for Camera Pose Estimation
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This dataset is a supplement of the paper DANCE: Domain Adaptation of Networks for Camera Pose Estimation: Learning Camera Pose Estimation Without Pose Labels [1]. The dataset contains a sample scene of a robot garage. The scene was captured by a Leica BLK360 laser scanner, and 16 scans were merged into a single point cloud of 118M colored points. The dataset also contains ~100k synthetically rendered images and scene coordinates generated form the point cloud. Furthermore, the dataset includes ~30k real photos of the space recorded by an iPhone 6 together with camera poses captured by a WorldViz system. [1] https://arxiv.org/abs/2111.14741
本数据集为论文《DANCE：基于网络相机的位姿估计领域自适应：无需位姿标签的相机位姿估计》[1]的补充材料。数据集包含一个机器人车间的典型场景样本。该场景通过徕卡BLK360激光扫描仪捕捉，并将16次扫描合并为一个包含118百万个彩色点的单一点云。此外，数据集还包含了约10万个通过合成渲染生成的图像以及从点云生成的场景坐标。进一步地，数据集还包括约3万个由iPhone 6拍摄的真实空间照片，以及由WorldViz系统捕获的相机位姿。[1] https://arxiv.org/abs/2111.14741
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