In the realm of digital creativity, our potential to craft intricate 3D worlds from imagination is
often hampered by the limitations of existing digital tools, which demand extensive expertise …

As it is hard to calibrate single-view RGB images in the wild, existing 3D human mesh
reconstruction (3DHMR) methods either use a constant large focal length or estimate one …

Learning 3D human-object interaction relation is pivotal to embodied AI and interaction
modeling. Most existing methods approach the goal by learning to predict isolated …

In this paper, we propose a new method, called DoubleCoverUDF, for extracting the zero
level-set from unsigned distance fields (UDFs). DoubleCoverUDF takes a learned UDF and …

Normal estimation for 3D point clouds is a fundamental task in 3D geometry processing. The
state-of-the-art methods rely on priors of fitting local surfaces learned from normal …

Reconstructing a continuous surface from a raw 3D point cloud is a challenging task. Recent
methods usually train neural networks to overfit on single point clouds to infer signed …

The rise of artificial intelligence generated content (AIGC) has been remarkable in the
language and image fields, but artificial intelligence (AI) generated three-dimensional (3D) …

We introduce a method for high-quality 3D reconstruction from multi-view images. Our
method uses a new point-based representation, the regularized dipole sum, which …

Convenient and high-fidelity 3D model reconstruction is crucial for industries like
manufacturing, medicine and archaeology. Current scanning approaches struggle with high …

3D Gaussian splatting models, as a novel explicit 3D representation, have been applied in
many domains recently, such as explicit geometric editing and geometry generation …