Welcome to the ETH3D Benchmark
ETH3D is part of the Robust Vision Challenge at CVPR 2018. Submit your algorithm for a chance to win $1000!
- 13 / 12 DSLR datasets for training / testing.
- 5 / 5 multi-cam rig videos for training / testing.
- 27 / 20 frames for two-view stereo training / testing.
- High-resolution (24 Mpx) DSLR images
- Multi-camera rig videos (4 cameras, ~13.6 Hz)
This webpage presents a multi-view stereo / 3D reconstruction benchmark covering a variety of indoor and outdoor scenes.
Ground truth geometry has been obtained using a high-precision laser scanner.
A DSLR camera as well as a synchronized multi-camera rig with varying field-of-view was used to capture images.
We offer the following challenges:
- 13 training and 12 test scenes (data / results) for high-resolution multi-view stereo with images recorded by the DSLR camera
- 5 training and 5 test videos (data / results) at ca. 13.6 Hz for low-resolution many-view stereo on video data recorded with the multi-camera rig
- 27 training and 20 test frames (data / results) for low-resolution two-view stereo on frames of the multi-camera rig
For a detailed description of the data and the format in which it is provided, see Documentation.
For downloading the datasets, go to Datasets.
Open source code related to the benchmark is available on GitHub.
This list is a summary, more details are available in the changelog.
- 2018-02-05: Open source release of the dataset pipeline.
- 2017-10-04: Extension with more data.
- 2017-07-19: Initial release of the dataset.
If you use our data in your research, please cite:
T. Schöps, J. L. Schönberger, S. Galliani, T. Sattler, K. Schindler, M. Pollefeys, A. Geiger, "A Multi-View Stereo Benchmark with High-Resolution Images and Multi-Camera Videos", Conference on Computer Vision and Pattern Recognition (CVPR), 2017. [Bibtex][PDF][Supplementary]
The data provided here is licensed under the Creative Commons Attribution-NonCommercial-ShareAlike 4.0 International License.