Unsupervised learning of 3D-aware generative adversarial networks (GANs) using only
collections of single-view 2D photographs has very recently made much progress. These 3D …

While the community of 3D point cloud generation has witnessed a big growth in recent
years, there still lacks an effective way to enable intuitive user control in the generation …

We study the problem of few-shot physically-aware articulated mesh generation. By
observing an articulated object dataset containing only a few examples, we wish to learn a …

We introduce PartGlot, a neural framework and associated architectures for learning
semantic part segmentation of 3D shape geometry, based solely on part referential …

We propose a novel technique for producing high-quality 3D models that match a given
target object image or scan. Our method is based on retrieving an existing shape from a …

In this work, we address the task of Language-Assisted 3D Shape Edits and Deformations
(which we name ChangeIt3D). Given a 3D representation of an object and free-form natural …

Natural language interaction is a promising direction for democratizing 3D shape design.
However, existing methods for text-driven 3D shape editing face challenges in producing …

Abstract 3D shape editing is widely used in a range of applications such as movie
production, computer games and computer aided design. It is also a popular research topic …

We propose OptCtrlPoints, a data‐driven framework designed to identify the optimal sparse
set of control points for reproducing target shapes using biharmonic 3D shape deformation …

Recent advances in 3D face stylization have made significant strides in few to zero-shot
settings. However the degree of stylization achieved by existing methods is often not …