1 to 7 of 7 Results
Oct 26, 2020 - OwnReality. To Each His Own Reality
Schepp, Moritz, 2020, "OwnReality API-only web application", https://doi.org/10.11588/data/KZHLS8, heiDATA, V1
This dataset contains the data platform for the research project "OwnReality. To Each His Own Reality". During the course of the project, data was gathered and entered into a database. In general, this platform allows the integration of that data into web based systems such as co... |
Sep 7, 2020 - IWR Visual Learning Lab
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 |
Sep 7, 2020 - IWR Visual Learning Lab
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 - IWR Visual Learning Lab
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... |
Sep 7, 2020 - IWR Visual Learning Lab
Brachmann, Eric, 2020, "Neural-Guided RANSAC for Estimating Epipolar Geometry [Data]", https://doi.org/10.11588/data/PCGYET, heiDATA, V1
Pre-computed sparse feature correspondences for pairs of images (outdoor and indoor) to reproduce the experiments described in our paper, particularly to train and evaluate NG-RANSAC. For more information, also see the code documentation: https://github.com/vislearn/ngransac |
Sep 7, 2020 - IWR Visual Learning Lab
Brachmann, Eric, 2020, "Expert Sample Consensus (ESAC) for Visual Re-Localization [Data]", https://doi.org/10.11588/data/GSJE9D, heiDATA, V1
Supplementary training data for visual camera re-localization, particularly pre-computed scene coordinates to the MSR 7Scenes dataset and the Standford 12Scenes dataset. We also provide pre-trained models of our method for the 7Scenes, 12Scenes, Dubrovnik and Aachen (day) dataset... |
Jul 31, 2020 - Cluster of Excellence - Asia and Europe in a Global Context
Arnold, Matthias; Dober, Agnes, 2020, "Cataloging Cultural Objects (CCO) – The CCO Commons examples in VRA Core 4 XML", https://doi.org/10.11588/data/KKTC9G, heiDATA, V1
“Cataloging Cultural Objects - a Guide to Describing Cultural Works and Their Images” (CCO) provides a data content standard for catalogers of cultural heritage. It is a guidebook for how to populate data elements and where to apply controlled vocabulary standards. The guide is f... |