Name
Abstract | ||
|---|---|---|
This paper introduces KeystoneDepth, the largest and most diverse collection of rectified historical stereo image pairs to date, consisting of tens of thousands of stereographs of people, events, objects, and scenes recorded between 1864 and 1966. Leveraging the Keystone-Mast Collection of stereographs from the California Museum of Photography, we apply multiple processing steps to produce clean stereo image pairs, complete with calibration data, rectification transforms, and disparity maps. We introduce a novel stereo rectification technique based on the unique properties of antique stereo cameras. To better visualize the results on 2D displays, we also introduce a self-supervised deep view synthesis technique trained on historical imagery. Our dataset is available at http://keystonedepth.cs.washington.edu/. |
Year | DOI | Venue |
|---|---|---|
2020 | 10.1109/3DV50981.2020.00056 | 2020 International Conference on 3D Vision (3DV) |
Keywords | DocType | ISSN |
Stereo vision,stereo image dataset,3D photography,disparity estimation,historical imagery | Conference | 2378-3826 |
ISBN | Citations | PageRank |
978-1-7281-8129-5 | 0 | 0.34 |
References | Authors | |
0 | 5 | |
Name | Order | Citations | PageRank |
|---|---|---|---|
| Xuan Luo | 1 | 30 | 10.84 |
| Yanmeng Kong | 2 | 0 | 0.34 |
| Jason Lawrence | 3 | 0 | 0.34 |
| Ricardo Martin-Brualla | 4 | 133 | 8.12 |
| Steven M. Seitz | 5 | 8729 | 495.13 |