Recent advancements in 3D object reconstruction from single images have primarily focused on improving the accuracy of object shapes. Yet, these techniques often fail to accurately capture the inter-relation between the object, ground, and camera. As a result, the reconstructed objects often appear floating or tilted when placed on flat surfaces. This limitation significantly affects 3D-aware image editing applications like shadow rendering and object pose manipulation. To address this issue, we introduce ORG (Object Reconstruction with Ground), a novel task aimed at reconstructing 3D object geometry in conjunction with the ground surface. Our method uses two compact pixel-level representations to depict the relationship between camera, object, and ground. Experiments show that the proposed ORG model can effectively reconstruct object-ground geometry on unseen data, significantly enhancing the quality of shadow generation and pose manipulation compared to conventional single-image 3D reconstruction techniques.

翻译：近年来，基于单幅图像的三维物体重建研究主要聚焦于提升物体形状的精确度。然而，这些技术往往未能准确捕捉物体、地面与相机之间的相互关系，导致重建后的物体置于平面时经常出现悬浮或倾斜现象。这一局限显著影响了阴影渲染和物体位姿操控等三维感知图像编辑应用的效果。为解决该问题，我们提出了ORG（带地面的物体重建）这一新任务，旨在联合重建三维物体几何与地表平面。我们的方法采用两种紧凑的像素级表征来描述相机、物体与地面间的空间关系。实验表明，所提出的ORG模型能够有效重建未见数据中的物体-地面几何结构，与传统单图像三维重建技术相比，显著提升了阴影生成与位姿操控的质量。