Improve 3D human reconstruction by using occupancy planes with OPlanes
Improve 3D human reconstruction by using occupancy planes with OPlanes
Occupancy Planes for Single-view RGB-D Human Reconstruction
arXiv paper abstract https://arxiv.org/abs/2208.02817
arXiv PDF paper https://arxiv.org/pdf/2208.02817.pdf
Single-view RGB-D human reconstruction with implicit functions is often formulated as per-point classification.
… The feature of each 3D location is then used to classify independently whether the corresponding 3D point is inside or outside the observed object.
This procedure leads to sub-optimal results because correlations between predictions for neighboring locations are only taken into account implicitly via the extracted features.
… propose the occupancy planes (OPlanes) representation, which enables to formulate single-view RGB-D human reconstruction as occupancy prediction on planes which slice through the camera’s view frustum.
Such a representation provides more flexibility than voxel grids and enables to better leverage correlations than per-point classification.
… observe a simple classifier based on the OPlanes representation to yield compelling results …
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