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DDL-MVS: Depth Discontinuity Learning for MVS Networks
[article]
2022
arXiv
pre-print
Traditional MVS methods have good accuracy but struggle with completeness, while recently developed learning-based multi-view stereo (MVS) techniques have improved completeness except accuracy being compromised. We propose depth discontinuity learning for MVS methods, which further improves accuracy while retaining the completeness of the reconstruction. Our idea is to jointly estimate the depth and boundary maps where the boundary maps are explicitly used for further refinement of the depth
arXiv:2203.01391v2
fatcat:wkuqjxurdzdk3ajb4qyzhfzmeq