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ETH3D Two-view Stereo
3D Keypoints
Stereo Matching
|...
License: CC BY-NC-SA 4.0

Overview

ETH3D two-view dataset contains 27 training and 20 test frames for low-resolution two-view
stereo on frames of the multi-camera rig.

Data Format

Format of two-view data

The two-view datasets provide stereo-rectified image pairs, i.e., for a given pixel in one
image the corresponding epipolar line in the other image is the image row having the same y-coordinate
as the pixel. These datasets, come with the cameras.txt
and images.txt files specifying the intrinsic
and extrinsic camera parameters of the images. See above for a description of their format.
In the two-view case all images are pre-undistorted, so their camera model is PINHOLE. This
model is defined in the camera models section.
We do not provide keypoint matches and triangulated keypoints for this type of data.

Furthermore,
the two-view datasets also come with a file calib.txt which is formatted according to the Middlebury
data format - version 3
. Note that those
files do not provide any information about the disparity range: the corresponding field is
set to the image width.

Training data

The ground truth follows the same format as the Middlebury stereo
benchmark, version 3. The ground truth disparity for the left image is provided as a file disp0GT.pfm
in the PFM format using little endian data. Therefore,
the ASCII header may look as follows, for example:

Pf
752 480
-1

The first line is always "Pf", indicating
a grayscale PFM image. The second line specifies the width and height of the image. The third
line is always "-1", indicating the use of little endian. After this header (where each line
is followed by a newline character), the ground truth disparity image follows in row-major
binary form as 4-byte floats. The rows are ordered from bottom to top. Positive infinity is
used for invalid values.

The occlusion mask for the left image is given as a file "mask0nocc.png".
Pixels without ground truth have the color (0, 0, 0). Pixels which are only observed by the
left image have the color (128, 128, 128). Pixels with are observed by both images have the
color (255, 255, 255). For the "non-occluded" evaluation, the evaluation is limited to the
pixels observed by both images.

Citation

Please use the following citation when referencing the dataset:

@inproceedings{schoeps2017cvpr,
  author = {Thomas Sch\"ops and Johannes L. Sch\"onberger and Silvano Galliani and Torsten
Sattler and Konrad Schindler and Marc Pollefeys and Andreas Geiger},
  title = {A Multi-View Stereo Benchmark with High-Resolution Images and Multi-Camera Videos},
  booktitle = {Conference on Computer Vision and Pattern Recognition (CVPR)},
  year = {2017}
}

License

CC BY-NC-SA 4.0

Data Summary
Type
Image,
Amount
--
Size
39.64MB
Provided by
ETH Zurich
ETH Zurich is a public research university in the city of Zürich, Switzerland.
| Amount -- | Size 39.64MB
ETH3D Two-view Stereo
3D Keypoints
Stereo Matching
License: CC BY-NC-SA 4.0

Overview

ETH3D two-view dataset contains 27 training and 20 test frames for low-resolution two-view
stereo on frames of the multi-camera rig.

Data Format

Format of two-view data

The two-view datasets provide stereo-rectified image pairs, i.e., for a given pixel in one
image the corresponding epipolar line in the other image is the image row having the same y-coordinate
as the pixel. These datasets, come with the cameras.txt
and images.txt files specifying the intrinsic
and extrinsic camera parameters of the images. See above for a description of their format.
In the two-view case all images are pre-undistorted, so their camera model is PINHOLE. This
model is defined in the camera models section.
We do not provide keypoint matches and triangulated keypoints for this type of data.

Furthermore,
the two-view datasets also come with a file calib.txt which is formatted according to the Middlebury
data format - version 3
. Note that those
files do not provide any information about the disparity range: the corresponding field is
set to the image width.

Training data

The ground truth follows the same format as the Middlebury stereo
benchmark, version 3. The ground truth disparity for the left image is provided as a file disp0GT.pfm
in the PFM format using little endian data. Therefore,
the ASCII header may look as follows, for example:

Pf
752 480
-1

The first line is always "Pf", indicating
a grayscale PFM image. The second line specifies the width and height of the image. The third
line is always "-1", indicating the use of little endian. After this header (where each line
is followed by a newline character), the ground truth disparity image follows in row-major
binary form as 4-byte floats. The rows are ordered from bottom to top. Positive infinity is
used for invalid values.

The occlusion mask for the left image is given as a file "mask0nocc.png".
Pixels without ground truth have the color (0, 0, 0). Pixels which are only observed by the
left image have the color (128, 128, 128). Pixels with are observed by both images have the
color (255, 255, 255). For the "non-occluded" evaluation, the evaluation is limited to the
pixels observed by both images.

Citation

Please use the following citation when referencing the dataset:

@inproceedings{schoeps2017cvpr,
  author = {Thomas Sch\"ops and Johannes L. Sch\"onberger and Silvano Galliani and Torsten
Sattler and Konrad Schindler and Marc Pollefeys and Andreas Geiger},
  title = {A Multi-View Stereo Benchmark with High-Resolution Images and Multi-Camera Videos},
  booktitle = {Conference on Computer Vision and Pattern Recognition (CVPR)},
  year = {2017}
}

License

CC BY-NC-SA 4.0

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