April 12, 2024, 4:46 a.m. | Jiang Wu, Rui Li, Haofei Xu, Wenxun Zhao, Yu Zhu, Jinqiu Sun, Yanning Zhang

cs.CV updates on arXiv.org arxiv.org

arXiv:2404.07992v1 Announce Type: new
Abstract: Matching cost aggregation plays a fundamental role in learning-based multi-view stereo networks. However, directly aggregating adjacent costs can lead to suboptimal results due to local geometric inconsistency. Related methods either seek selective aggregation or improve aggregated depth in the 2D space, both are unable to handle geometric inconsistency in the cost volume effectively. In this paper, we propose GoMVS to aggregate geometrically consistent costs, yielding better utilization of adjacent geometries. More specifically, we correspond and …

abstract aggregation arxiv consistent cost costs cs.cv however networks results role space type view

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