As information exists in various modalities in real world, effective interaction and fusion
among multimodal information plays a key role for the creation and perception of multimodal …

In this paper, we present a novel diffusion model called that generates multiview-consistent
images from a single-view image. Using pretrained large-scale 2D diffusion models, recent …

We introduce GRM, a large-scale reconstructor capable of recovering a 3D asset from
sparse-view images in around 0.1 s. GRM is a feed-forward transformer-based model that …

In this work, we present a novel framework built to simplify 3D asset generation for amateur
users. To enable interactive generation, our method supports a variety of input modalities …

Recent years have seen remarkable progress in deep learning powered visual content
creation. This includes deep generative 3D-aware image synthesis, which produces high …

Efficient generation of 3D digital humans is important in several industries including virtual
reality social media and cinematic production. 3D generative adversarial networks (GANs) …

Diffusion-based methods have shown impressive visual results in the text-to-image domain.
They first learn a latent space using an autoencoder, then run a denoising process on the …

In this paper, we introduce a novel 3D-aware image generation method that leverages 2D
diffusion models. We formulate the 3D-aware image generation task as multiview 2D image …

We propose\textbf {DMV3D}, a novel 3D generation approach that uses a transformer-based
3D large reconstruction model to denoise multi-view diffusion. Our reconstruction model …

Abstract We present Text2Tex, a novel method for generating high-quality textures for 3D
meshes from the given text prompts. Our method incorporates inpainting into a pre-trained …