Abstract We introduce the Segment Anything (SA) project: a new task, model, and dataset for
image segmentation. Using our efficient model in a data collection loop, we built the largest …

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 …

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 …

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 …

We propose MVDream, a multi-view diffusion model that is able to generate geometrically
consistent multi-view images from a given text prompt. By leveraging image diffusion models …

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 …

We present an approach to reconstruct humans and track them over time. At the core of our
approach, we propose a fully" transformerized" version of a network for human mesh …

Recent advancements in 3D reconstruction from single images have been driven by the
evolution of generative models. Prominent among these are methods based on Score …

We propose the first Large Reconstruction Model (LRM) that predicts the 3D model of an
object from a single input image within just 5 seconds. In contrast to many previous methods …

Text-to-3D generation has shown rapid progress in recent days with the advent of score
distillation, a methodology of using pretrained text-to-2D diffusion models to optimize neural …