Enhanced feature pyramid for multi-view stereo with adaptive correlation cost volume
Author:
Funder
Fundamental Research Funds for the Central Universities
National Natural Science Foundation of China
Publisher
Springer Science and Business Media LLC
Link
https://link.springer.com/content/pdf/10.1007/s10489-024-05574-z.pdf
Reference40 articles.
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2. Abbaszadeh Shahri A, Shan C, Larsson S (2022) A novel approach to uncertainty quantification in groundwater table modeling by automated predictive deep learning. Nat Resour Res 31(3):1351–1373. https://doi.org/10.1007/s11053-022-10051-w
3. Cai Y, Li L, Wang D et al (2023) Mfnet: Multi-level fusion aware feature pyramid based multi-view stereo network for 3d reconstruction. Appl Intell 53(4):4289–4301. https://doi.org/10.1007/s10489-022-03754-3
4. Campbell ND, Vogiatzis G, Hernández C et al (2008) Using multiple hypotheses to improve depth-maps for multi-view stereo. In: Computer vision–ECCV 2008: 10th European Conference on Computer Vision, Marseille, France, October 12-18, 2008, Proceedings, Part I 10. Springer, pp 766–779
5. Chen PH, Yang HC, Chen KW et al (2020) Mvsnet++: learning depth-based attention pyramid features for multi-view stereo. IEEE Trans Image Process 29:7261–7273. https://doi.org/10.1109/TIP.2020.3000611
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