Deep neural networks (DNNs) have shown remarkable performance improvements on
vision-related tasks such as object detection or image segmentation. Despite their success …

Automatic 3D content creation has achieved rapid progress recently due to the availability of
pre-trained, large language models and image diffusion models, forming the emerging topic …

As several industries are moving towards modeling massive 3D virtual worlds, the need for
content creation tools that can scale in terms of the quantity, quality, and diversity of 3D …

Natural language processing and 2D vision models have attained remarkable proficiency on
many tasks primarily by escalating the scale of training data. However, 3D vision tasks have …

Denoising diffusion models (DDMs) have shown promising results in 3D point cloud
synthesis. To advance 3D DDMs and make them useful for digital artists, we require (i) high …

We present a method that achieves state-of-the-art results for synthesizing novel views of
complex scenes by optimizing an underlying continuous volumetric scene function using a …

Generative Adversarial Networks (GANs) have achieved impressive results in various image
synthesis tasks, and are becoming a hot topic in computer vision research because of the …

We present a method that synthesizes novel views of complex scenes by interpolating a
sparse set of nearby views. The core of our method is a network architecture that includes a …

We introduce DMTet, a deep 3D conditional generative model that can synthesize high-
resolution 3D shapes using simple user guides such as coarse voxels. It marries the merits …

In this work, we develop intuitive controls for editing the style of 3D objects. Our framework,
Text2Mesh, stylizes a 3D mesh by predicting color and local geometric details which …