@inproceedings{
he2024alphatablets,
title={AlphaTablets: A Generic Plane Representation for 3D Planar Reconstruction from Monocular Videos},
author={Yuze He and Wang Zhao and Shaohui Liu and Yubin Hu and Yushi Bai and Yu-Hui Wen and Yong-jin Liu},
booktitle={The Thirty-eighth Annual Conference on Neural Information Processing Systems},
year={2024},
url={https://openreview.net/forum?id=7rrJQ9iWoX}
}
We introduce AlphaTablets, a novel and generic representation of 3D planes that features continuous 3D surface and precise boundary delineation. By representing 3D planes as rectangles with alpha channels, AlphaTablets combine the advantages of current 2D and 3D plane representations, enabling accurate, consistent and flexible modeling of 3D planes. We derive differentiable rasterization on top of AlphaTablets to efficiently render 3D planes into images, and propose a novel bottom-up pipeline for 3D planar reconstruction from monocular videos. Starting with 2D superpixels and geometric cues from pre-trained models, we initialize 3D planes as AlphaTablets and optimize them via differentiable rendering. An effective merging scheme is introduced to facilitate the growth and refinement of AlphaTablets. Through iterative optimization and merging, we reconstruct complete and accurate 3D planes with solid surfaces and clear boundaries. Extensive experiments on the ScanNet dataset demonstrate state-of-the-art performance in 3D planar reconstruction, underscoring the great potential of AlphaTablets as a generic 3D plane representation for various applications.
AlphaTablets: A Generic Plane Representation for 3D Planar Reconstruction from Monocular Videos
Yuze He Wang Zhao Shaohui Liu Yubin Hu Yushi Bai Yu-Hui Wen Yong-jin Liu