Although the recent rapid evolution of 3D generative neural networks greatly improves 3D
shape generation, it is still not convenient for ordinary users to create 3D shapes and control …

Abstract 3D shape modeling is labor-intensive, time-consuming, and requires years of
expertise. To facilitate 3D shape modeling, we propose a 3D shape generation network that …

Significant progress has recently been made in creative applications of large pre-trained
models for downstream tasks in 3D vision, such as text-to-shape generation. This motivates …

Generating realistic 3D scenes is challenging due to the complexity of room layouts and
object geometries. We propose a sketch based knowledge enhanced diffusion architecture …

With the emergence of AR/VR 3D models are in tremendous demand. However
conventional 3D modeling with Computer-Aided Design software requires much expertise …

In this paper, we propose Img2CAD, the first approach to our knowledge that uses 2D image
inputs to generate CAD models with editable parameters. Unlike existing AI methods for 3D …

Recently, image-to-3D approaches have achieved significant results with a natural image as
input. However, it is not always possible to access these enriched color input samples in …

Denoising diffusion models have demonstrated tremendous success in modeling data
distributions and synthesizing high-quality samples. In the 2D image domain, they have …