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Middlebury Dataset
- paperswithcode.com
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EmailClick to copy linkLink copiedCiteDaniel Scharstein; Richard Szeliski, Middlebury Dataset [Dataset]. https://paperswithcode.com/dataset/middleburyAuthorsDaniel Scharstein; Richard SzeliskiArea coveredMiddleburyDescriptionThe Middlebury Stereo dataset consists of high-resolution stereo sequences with complex geometry and pixel-accurate ground-truth disparity data. The ground-truth disparities are acquired using a novel technique that employs structured lighting and does not require the calibration of the light projectors.
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Velocity Field Estimation on Density-Driven Solute Transport With a...
- heidata.uni-heidelberg.de
mp4, txt, zipUpdated May 21, 2019ShareFacebookTwitterEmailClick to copy linkLink copiedCitePhilipp J. Kreyenberg; Hannes H. Bauser; Kurt Roth; Philipp J. Kreyenberg; Hannes H. Bauser; Kurt Roth (2019). Velocity Field Estimation on Density-Driven Solute Transport With a Convolutional Neural Network [Dataset] [Dataset]. http://doi.org/10.11588/DATA/7NEEKFtxt(4591), zip(18948045), mp4(22238180), zip(16673949866)Available download formatsUnique identifierhttps://doi.org/10.11588/DATA/7NEEKFDataset updatedMay 21, 2019Dataset provided byheiDATAAuthorsPhilipp J. Kreyenberg; Hannes H. Bauser; Kurt Roth; Philipp J. Kreyenberg; Hannes H. Bauser; Kurt RothLicensehttps://heidata.uni-heidelberg.de/api/datasets/:persistentId/versions/1.0/customlicense?persistentId=doi:10.11588/DATA/7NEEKFhttps://heidata.uni-heidelberg.de/api/datasets/:persistentId/versions/1.0/customlicense?persistentId=doi:10.11588/DATA/7NEEKF
DescriptionThis data set accompanies the manuscript ‘Velocity Field Estimation on Density-Driven Solute Transport With a Convolutional Neural Network’. Concentration fields are stored as portable pixel maps (.ppm) and flow fields are stored in the Middlebury .flo file format (http://vision.middlebury.edu/flow/code/flow-code/README.txt).
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Middlebury error rates of different algorithms (Error Threshold = 1).
- plos.figshare.com
xlsUpdated Jun 5, 2023ShareFacebookTwitterEmailClick to copy linkLink copiedCiteXingzheng Wang; Yushi Tian; Haoqian Wang; Yongbing Zhang (2023). Middlebury error rates of different algorithms (Error Threshold = 1). [Dataset]. http://doi.org/10.1371/journal.pone.0162939.t001xlsAvailable download formatsUnique identifierhttps://doi.org/10.1371/journal.pone.0162939.t001Dataset updatedJun 5, 2023Dataset provided byPLOS ONEAuthorsXingzheng Wang; Yushi Tian; Haoqian Wang; Yongbing ZhangLicenseAttribution 4.0 (CC BY 4.0)https://creativecommons.org/licenses/by/4.0/
License information was derived automaticallyDescriptionMiddlebury error rates of different algorithms (Error Threshold = 1).
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FacebookTwitterEmailThe Middlebury Stereo dataset consists of high-resolution stereo sequences with complex geometry and pixel-accurate ground-truth disparity data. The ground-truth disparities are acquired using a novel technique that employs structured lighting and does not require the calibration of the light projectors.