1 to 10 of 26 Results
Jan 7, 2022
Brachmann, Eric, 2020, "DSAC* Visual Re-Localization [Data]", https://doi.org/10.11588/data/N07HKC, heiDATA, V2
Supplementary training data for visual camera re-localization, particularly rendered depth maps to be used in combination with the MSR 7Scenes dataset, and the Stanford 12Scenes dataset, as well as precomputed camera coordinate files for both aforementioned datasets. For more inf... |
Jan 7, 2022 -
DSAC* Visual Re-Localization [Data]
Gzip Archive - 1.6 GB -
MD5: 3ed5ec292f6aa5b8b3d8be47c103d5f4
|
Sep 7, 2020
Brachmann, Eric, 2020, "Differentiable RANSAC (DSAC) for Visual Re-Localization [Data]", https://doi.org/10.11588/data/3JVZSH, heiDATA, V1
Pre-trained models of our camera re-localization method for the MSR 7Scenes dataset. For more information, also see the code documentation: https://github.com/cvlab-dresden/DSAC |
Gzip Archive - 3.9 GB -
MD5: 60faa75a1b48608ebf0afc417c12716d
|
Sep 7, 2020
Brachmann, Eric, 2020, "DSAC++ Visual Camera Re-Localization [Data]", https://doi.org/10.11588/data/EGCMUU, heiDATA, V1
Supplementary training data for visual camera re-localization, particularly rendered depth maps to be used in combination with the Cambridge Landmarks dataset. We also provide pre-trained models of our method for the MSR 7Scenes dataset and the Cambridge Landmarks dataset. For mo... |
Sep 7, 2020 -
DSAC++ Visual Camera Re-Localization [Data]
ZIP Archive - 6.1 GB -
MD5: 778623d521d814881e93e05df2987627
|
Sep 7, 2020 -
DSAC++ Visual Camera Re-Localization [Data]
Gzip Archive - 6.1 GB -
MD5: 3c4f0e198fd2cc1f153c4378c1265269
|
Sep 7, 2020
Brachmann, Eric, 2020, "6D Object Pose Estimation using 3D Object Coordinates [Data]", https://doi.org/10.11588/data/V4MUMX, heiDATA, V1
Supplementary training data and binaries for 6D object pose estimation, particularly a dataset of 20 objects under various lighting conditions with RGB-D images, ground truth poses and segmentation as well as 3D models. Additionally, a collection of RGB-D images showing office ba... |
ZIP Archive - 4.4 GB -
MD5: e59d05612be04c6999ae0a62ce82b917
|
ZIP Archive - 1.1 GB -
MD5: d9c531e3d1c2505d6fc74c994722d956
|