Human motion generation aims to generate natural human pose sequences and shows
immense potential for real-world applications. Substantial progress has been made recently …

Abstract Generative Adversarial Networks (GANs) are a type of deep learning architecture
that uses two networks namely a generator and a discriminator that, by competing against …

Abstract We introduce Zero-1-to-3, a framework for changing the camera viewpoint of an
object given just a single RGB image. To perform novel view synthesis in this …

In this work we introduce Wonder3D a novel method for generating high-fidelity textured
meshes from single-view images with remarkable efficiency. Recent methods based on the …

Single image 3D reconstruction is an important but challenging task that requires extensive
knowledge of our natural world. Many existing methods solve this problem by optimizing a …

We introduce MVDream, a diffusion model that is able to generate consistent multi-view
images from a given text prompt. Learning from both 2D and 3D data, a multi-view diffusion …

We present Shap-E, a conditional generative model for 3D assets. Unlike recent work on 3D
generative models which produce a single output representation, Shap-E directly generates …

Massive data corpora like WebText, Wikipedia, Conceptual Captions, WebImageText, and
LAION have propelled recent dramatic progress in AI. Large neural models trained on such …

Recent advancements in open-world 3D object generation have been remarkable with
image-to-3D methods offering superior fine-grained control over their text-to-3D …

Recent developments in the field of artificial intelligence (AI) have enabled new paradigms
of machine processing, shifting from data-driven, discriminative AI tasks toward …