Get 3D scene by using view-dependent colors and constraints on geometry and photography with Yu
Get 3D scene by using view-dependent colors and constraints on geometry and photography with Yu
Improving Neural Indoor Surface Reconstruction with Mask-Guided Adaptive Consistency Constraints
arXiv paper abstract https://arxiv.org/abs/2309.09739
arXiv PDF paper https://arxiv.org/pdf/2309.09739.pdf
3D scene reconstruction from 2D images has been a long-standing task.
Instead of estimating per-frame depth maps and fusing them in 3D, recent research leverages the neural implicit surface
... Equipped with data-driven pre-trained geometric cues, these methods have demonstrated promising performance. However, inaccurate prior estimation ... can lead to suboptimal reconstruction quality ... in ... geometrically complex regions.
... propose a two-stage training process, decouple view-dependent and view-independent colors, and leverage two novel consistency constraints to enhance detail reconstruction performance
... introduce an essential mask scheme to adaptively influence the selection of supervision constraints, thereby improving performance in a self-supervised paradigm.
... show the capability of reducing the interference from prior estimation errors and achieving high-quality scene reconstruction with rich geometric details.
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