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

Author:

Mehl Lukas1,Schmalfuss Jenny1,Jahedi Azin1,Nalivayko Yaroslava1,Bruhn Andrés1

Affiliation:

1. Institute for Visualization and Interactive Systems, University of Stuttgart

Funder

Deutsche Forschungsgemeinschaft (DFG, German Research Foundation)

Publisher

IEEE

Reference53 articles.

1. Determining Optical Flow

2. Accurate and Efficient Stereo Processing by Semi-Global Matching and Mutual Information

3. A Variational Method for Scene Flow Estimation from Stereo Sequences

4. FlowFormer: a transformer architecture for optical flow;huang;Proc European Conference on Computer Vision (ECCV),2022

5. GANet: Guided aggregation net for end-to-end stereo matching;zhang;Proc IEEE/CVF Conference on Computer Vision and Pattern Recognition (CVPR),2019

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1. Detection Defenses: An Empty Promise against Adversarial Patch Attacks on Optical Flow;2024 IEEE/CVF Winter Conference on Applications of Computer Vision (WACV);2024-01-03

2. Lightweight Optical Flow Estimation Using 1D Matching;IEEE Access;2024

3. CroCo v2: Improved Cross-view Completion Pre-training for Stereo Matching and Optical Flow;2023 IEEE/CVF International Conference on Computer Vision (ICCV);2023-10-01

4. Distracting Downpour: Adversarial Weather Attacks for Motion Estimation;2023 IEEE/CVF International Conference on Computer Vision (ICCV);2023-10-01

5. Toward High-Quality Real-Time Video Denoising With Pseudo Temporal Fusion Network;IEEE Access;2023

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