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Adaptive Learning for Multi-view Stereo Reconstruction
April 9, 2024, 4:47 a.m. | Qinglu Min, Jie Zhao, Zhihao Zhang, Chen Min
cs.CV updates on arXiv.org arxiv.org
Abstract: Deep learning has recently demonstrated its excellent performance on the task of multi-view stereo (MVS). However, loss functions applied for deep MVS are rarely studied. In this paper, we first analyze existing loss functions' properties for deep depth based MVS approaches. Regression based loss leads to inaccurate continuous results by computing mathematical expectation, while classification based loss outputs discretized depth values. To this end, we then propose a novel loss function, named adaptive Wasserstein loss, …
abstract analyze arxiv continuous cs.cv deep learning functions however leads loss paper performance regression results type view
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