Get 3D scene from many images with holes fixed by fusion with depth priors with Attentive_DF_Prior
Get 3D scene from many images with holes fixed by fusion with depth priors with Attentive_DF_Prior
Learning Neural Implicit through Volume Rendering with Attentive Depth Fusion Priors
arXiv paper abstract https://arxiv.org/abs/2310.11598
arXiv PDF paper https://arxiv.org/pdf/2310.11598.pdf
Project page https://machineperceptionlab.github.io/Attentive_DF_Prior
… neural implicit representations has … remarkable performance in 3D reconstruction from multi-view images … However … suffers from incomplete depth at holes and unawareness of occluded structures
… propose to learn neural implicit representations from multi-view RGBD images through volume rendering with an attentive depth fusion prior.
… prior allows neural networks to perceive coarse 3D structures from the Truncated Signed Distance Function (TSDF) fused from all depth images available for rendering.
The TSDF enables accessing the missing depth at holes on one depth image and the occluded parts that are invisible from the current view.
By introducing a novel attention mechanism, … allow neural networks to directly use the depth fusion prior with the inferred occupancy as the learned implicit function.
… show … superiority over the latest neural implicit methods …
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