A NEW STEREO DENSE MATCHING BENCHMARK DATASET FOR DEEP LEARNING

14 citations as recorded by crossref.

1. Binocular Stereo Vision in Remote Sensing: A Review X. Li et al. https://doi.org/10.3390/rs18101480
2. CSStereo: A UAV scenarios stereo matching network enhanced with contrastive learning and feature selection X. Cao et al. https://doi.org/10.1016/j.jag.2024.104189
3. Hierarchical Domain Adaptation Framework for Disparity Estimation in Optical Satellite Stereo Imagery: Bridging Spatiotemporal-Sensor Heterogeneity G. Zhang et al. https://doi.org/10.1109/TGRS.2025.3574984
4. HMSM-Net: Hierarchical multi-scale matching network for disparity estimation of high-resolution satellite stereo images S. He et al. https://doi.org/10.1016/j.isprsjprs.2022.04.020
5. MFC-CNN: A Deep Learning Framework for Urban Building Height Estimation From GF-7 Imagery D. Cao et al. https://doi.org/10.1109/TGRS.2026.3653515
6. UAVStereo: A Multiple Resolution Dataset for Stereo Matching in UAV Scenarios X. Zhang et al. https://doi.org/10.1109/JSTARS.2023.3257489
7. An evaluation of Deep Learning based stereo dense matching dataset shift from aerial images and a large scale stereo dataset T. Wu et al. https://doi.org/10.1016/j.jag.2024.103715
8. Towards robust disparity estimation in satellite stereo imagery: a new high-quality benchmark dataset and a metadata-informed multi-range geometric encoding network G. Zhang et al. https://doi.org/10.1016/j.isprsjprs.2026.03.017
9. Edge-Preserving Stereo Matching Using LiDAR Points and Image Line Features S. Zou et al. https://doi.org/10.1109/LGRS.2023.3239030
10. Improving Least-Squares Stereo Matching by Using Different Reference Points H. Sadeq https://doi.org/10.1007/s12524-023-01699-9
11. A GF-based multi-source multi-temporal satellite benchmark for binocular disparity estimation Y. Wang et al. https://doi.org/10.1080/10095020.2026.2628419
12. WHU-Stereo: A Challenging Benchmark for Stereo Matching of High-Resolution Satellite Images S. Li et al. https://doi.org/10.1109/TGRS.2023.3245205
13. DualRecon: Building 3D Reconstruction from Dual-View Remote Sensing Images R. Shao et al. https://doi.org/10.3390/rs17233793
14. Improving Disparity Consistency With Self-Refined Cost Volumes for Deep Learning-Based Satellite Stereo Matching J. Kim et al. https://doi.org/10.1109/JSTARS.2025.3555424