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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



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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