Spring: A High-Resolution High-Detail Dataset and Benchmark for Scene Flow, Optical Flow and Stereo (doi:10.18419/darus-3376)

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Document Description

Citation

Title:

Spring: A High-Resolution High-Detail Dataset and Benchmark for Scene Flow, Optical Flow and Stereo

Identification Number:

doi:10.18419/darus-3376

Distributor:

DaRUS

Date of Distribution:

2023-03-14

Version:

2

Bibliographic Citation:

Mehl, Lukas; Schmalfuss, Jenny; Jahedi, Azin; Nalivayko, Yaroslava; Bruhn, Andrés, 2023, "Spring: A High-Resolution High-Detail Dataset and Benchmark for Scene Flow, Optical Flow and Stereo", https://doi.org/10.18419/darus-3376, DaRUS, V2

Study Description

Citation

Title:

Spring: A High-Resolution High-Detail Dataset and Benchmark for Scene Flow, Optical Flow and Stereo

Identification Number:

doi:10.18419/darus-3376

Authoring Entity:

Mehl, Lukas (Institute for Visualization and Interactive Systems, University of Stuttgart)

Schmalfuss, Jenny (Institute for Visualization and Interactive Systems, University of Stuttgart)

Jahedi, Azin (Institute for Visualization and Interactive Systems, University of Stuttgart)

Nalivayko, Yaroslava (Institute for Visualization and Interactive Systems, University of Stuttgart)

Bruhn, Andrés (Institute for Visualization and Interactive Systems, University of Stuttgart)

Grant Number:

251654672

Distributor:

DaRUS

Access Authority:

Bruhn, Andrés

Depositor:

Mehl, Lukas

Date of Deposit:

2023-03-08

Holdings Information:

https://doi.org/10.18419/darus-3376

Study Scope

Keywords:

Computer and Information Science, Computer Vision, Optical Flow, Computer Stereo Vision, Benchmark

Abstract:

The Spring dataset contains files for scene flow, optical flow and stereo estimation. For easier handling, we organized them into sub-directories: </br> <i>train</i> split: <ul> <li><code>train_frame_left.zip</code>: left camera frames</li> <li><code>train_frame_right.zip</code>: right camera frames</li> <li><code>train_disp1_left.zip</code>: left-to-right disparity in the reference frame</li> <li><code>train_disp1_right.zip</code>: right-to-left disparity in the reference frame</li> <li><code>train_disp2_FW_left.zip</code>: left-to-right disparity in the future/forward target frame</li> <li><code>train_disp2_BW_left.zip</code>: left-to-right disparity in the past/backward target frame</li> <li><code>train_disp2_FW_right.zip</code>: right-to-left disparity in the future/forward target frame</li> <li><code>train_disp2_BW_right.zip</code>: right-to-left disparity in the past/backward target frame</li> <li><code>train_flow_FW_left.zip</code>: left forward optical flow</li> <li><code>train_flow_BW_left.zip</code>: left backward optical flow</li> <li><code>train_flow_FW_right.zip</code>: right forward optical flow</li> <li><code>train_flow_BW_right.zip</code>: right backward optical flow</li> <li><code>train_cam_data.zip</code>: camera data: intrinsics, extrinsics, focal distance</li> <li><code>train_maps.zip</code>: additional maps: detail, match, rigid, sky</li> </ul> <i>test</i> split: <ul> <li><code>test_frame_left.zip</code>: left camera frames</li> <li><code>test_frame_right.zip</code>: right camera frames</li> <li><code>test_cam_data.zip</code>: camera data: intrinsics</li> </ul> </br> File formats: <ul> <li>images and maps are given in png format</li> <li>optical flow files are given in HDF5 file format and named <code>.flo5</code></li> <li>disparity files are given in HDF5 file format and named <code>.dsp5</code></li> </ul> For the project website see <a href="https://spring-benchmark.org">spring-benchmark.org</a>.

Methodology and Processing

Sources Statement

Data Sources:

The Spring movie assets (https://cloud.blender.org/spring) by Blender Foundation are licensed under CC BY 4.0

Data Access

Other Study Description Materials

Related Publications

Citation

Title:

Lukas Mehl, Jenny Schmalfuss, Azin Jahedi, Yaroslava Nalivayko, Andrés Bruhn: Spring: A High-Resolution High-Detail Dataset and Benchmark for Scene Flow, Optical Flow and Stereo. Proc. IEEE/CVF Conference on Computer Vision and Pattern Recognition (CVPR), 2023.

Identification Number:

2303.01943

Bibliographic Citation:

Lukas Mehl, Jenny Schmalfuss, Azin Jahedi, Yaroslava Nalivayko, Andrés Bruhn: Spring: A High-Resolution High-Detail Dataset and Benchmark for Scene Flow, Optical Flow and Stereo. Proc. IEEE/CVF Conference on Computer Vision and Pattern Recognition (CVPR), 2023.

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test_frame_left.zip

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train_cam_data.zip

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train_flow_BW_left.zip

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train_maps.zip

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