MSP-MVS: Multi-granularity Segmentation Prior Guided Multi-View Stereo
<|reference_start|>MSP-MVS: Multi-granularity Segmentation Prior Guided Multi-View Stereo: Reconstructing textureless areas in MVS poses challenges due to the absence of reliable pixel correspondences within fixed patch. Although certain methods employ patch deformation to expand the receptive field, their patches mistakenly skip depth edges to calculate areas with depth discontinuity, thereby causing ambiguity. Consequently, we introduce Multi-granularity Segmentation Prior Multi-View Stereo (MSP-MVS). Specifically, we first propose multi-granularity segmentation prior by integrating multi-granularity depth edges to restrict patch deformation within homogeneous areas. Moreover, we present anchor equidistribution that bring deformed patches with more uniformly distributed anchors to ensure an adequate coverage of their own homogeneous areas. Furthermore, we introduce iterative local search optimization to represent larger patch with sparse representative candidates, significantly boosting the expressive capacity for each patch. The state-of-the-art results on ETH3D and Tanks & Temples benchmarks demonstrate the effectiveness and robust generalization ability of our proposed method.<|reference_end|>
@article{yuan2024msp-mvs:,
    title={MSP-MVS: Multi-granularity Segmentation Prior Guided Multi-View Stereo},
    author={Zhenlong Yuan, Cong Liu, Fei Shen, Zhaoxin Li, Tianlu Mao and Zhaoqi
  Wang},
    journal={arXiv preprint arXiv:2407.19323},
    year={2024},
    archivePrefix={arXiv},
    eprint={2407.19323},
    primaryClass={cs.CV}
}