Get 3D shape of object by combining neural reconstruction and multiple views with C2F2NeUS
Get 3D shape of object by combining neural reconstruction and multiple views with C2F2NeUS
C2F2NeUS: Cascade Cost Frustum Fusion for High Fidelity and Generalizable Neural Surface Reconstruction
arXiv paper abstract https://arxiv.org/abs/2306.10003
arXiv PDF paper https://arxiv.org/pdf/2306.10003.pdf
There is ... effort to combine ... multi-view stereo (MVS) and neural implicit surface (NIS), in scene reconstruction from sparse views.
... introduce a novel integration scheme that combines the multi-view stereo with neural signed distance function representations, which potentially overcomes the limitations of both methods.
MVS uses per-view depth estimation and cross-view fusion to generate accurate surface, while NIS relies on a common coordinate volume.
... propose to construct per-view cost frustum for finer geometry estimation, and then fuse cross-view frustums and estimate the implicit signed distance functions to tackle noise and hole issues.
... apply a cascade frustum fusion strategy to effectively captures global-local information and structural consistency.
... method reconstructs robust surfaces and outperforms existing state-of-the-art methods.
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