The ICL-NUIM dataset aims at benchmarking RGB-D, Visual Odometry and SLAM algorithms. Two different scenes (the living room and the office room scene) are provided with ground truth. Living room has 3D surface ground truth together with the depth-maps as well as camera poses and as a result perfectly suits not just for benchmarking camera trajectory but also reconstruction. Office room scene comes with only trajectory data and does not have any explicit 3D model with it.

All data is compatible with the evaluation tools available for the TUM RGB-D dataset, and if your system can take TUM RGB-D format PNGs as input, the authors’ TUM RGB-D Compatible data will also work (given the correct camera parameters).