AlphaTablets: A Generic Plane Representation for 3D Planar Reconstruction from Monocular Videos

TL;DR

AlphaTablets introduces a new 3D plane representation using rectangles with alpha channels, enabling accurate and flexible 3D planar reconstruction from monocular videos with state-of-the-art results.

Contribution

The paper presents AlphaTablets, a novel, differentiable, rectangle-based 3D plane representation that improves reconstruction accuracy and boundary delineation from monocular videos.

Findings

Achieves state-of-the-art 3D planar reconstruction on ScanNet

Enables accurate boundary and surface modeling of planes

Demonstrates effective merging and refinement of AlphaTablets

Abstract

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. Project page is available at: https://hyzcluster.github.io/alphatablets