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

翻译：我们提出了AlphaTablets，这是一种新颖且通用的三维平面表示方法，具有连续的三维表面和精确的边界描绘。通过将三维平面表示为带有Alpha通道的矩形，AlphaTablets结合了当前二维和三维平面表示方法的优点，能够实现准确、一致且灵活的三维平面建模。我们在AlphaTablets基础上推导了可微分栅格化方法，以高效地将三维平面渲染到图像中，并提出了一种新颖的自底向上流程，用于从单目视频进行三维平面重建。从二维超像素和预训练模型提供的几何线索出发，我们将三维平面初始化为AlphaTablets，并通过可微分渲染对其进行优化。我们引入了一种有效的合并方案，以促进AlphaTablets的生长和细化。通过迭代优化与合并，我们重建出具有坚实表面和清晰边界的完整且精确的三维平面。在ScanNet数据集上进行的大量实验证明了该方法在三维平面重建方面达到了最先进的性能，凸显了AlphaTablets作为一种通用三维平面表示方法在各种应用中的巨大潜力。项目页面位于：https://hyzcluster.github.io/alphatablets