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Semi-supervised Deep Multi-view Stereo. (arXiv:2207.11699v2 [cs.CV] UPDATED)
Aug. 29, 2022, 1:14 a.m. | Hongbin Xu, Zhipeng Zhou, Weitao Chen, Baigui Sun, Hao Li, Wenxiong Kang
cs.CV updates on arXiv.org arxiv.org
Significant progress has been witnessed in learning-based Multi-view Stereo
(MVS) of supervised and unsupervised settings. To combine their respective
merits in accuracy and completeness, meantime reducing the demand for expensive
labeled data, this paper explores a novel semi-supervised setting of
learning-based MVS problem that only a tiny part of the MVS data is attached
with dense depth ground truth. However, due to huge variation of scenarios and
flexible setting in views, semi-supervised MVS problem (Semi-MVS) may break the
basic assumption …
More from arxiv.org / cs.CV updates on arXiv.org
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