This folder contains the reconstructions used in the reconstruction benchmark in the paper. For each sequence, we provide:
- The input data
- Images: hardware synchronised camera images from the three Alphasense cameras
- Vilens_slam: undistorted lidar point cloud obtained from VILENS-SLAM. The timestamps are synchronised with the images with motion undistortion.
- T_gt_lidar.txt: the global transform between the lidar map and the ground truth map in). This allows one to compare the reconstruction with the ground truth in a single coordinate system. -Note 1: the raw point cloud is 10 Hz and raw camera is 20 Hz. Here, the point cloud provided comes from the pose-graph SLAM where a node is spawned every 1 metre travelled. The resultant frequency of the camera image and lidar cloud provided is about 1 Hz.
- The reconstructions
- lidar_cloud_merged_error.pcd: merged lidar cloud file.
- nerfacto_cloud_metric_gt_frame_error.pcd: exported point cloud from nerfacto.
- openmvs_dense_cloud_gt_frame_error.pcd: dense MVS point cloud from OpenMVS.
- Note 1: all reconstruction are coloured by point-to-point distance to the ground truth, i.e. reconstruction errors.
- Note 2: all reconstructions are filtered by the ground truth’s occupancy map gt_cloud.bt to avoid penalising points in the unknown space. This is described in SiLVR section V.C.2