The field of visual computing is rapidly advancing due to the emergence of generative
artificial intelligence (AI), which unlocks unprecedented capabilities for the generation …

Various techniques have been developed and introduced to address the pressing need to
create three-dimensional (3D) content for advanced applications such as virtual reality and …

Abstract We introduce Adversarial Diffusion Distillation (ADD), a novel training approach that
efficiently samples large-scale foundational image diffusion models in just 1–4 steps while …

Modeling and re-rendering dynamic 3D scenes is a challenging task in 3D vision. Prior
approaches build on NeRF and rely on implicit representations. This is slow since it requires …

Abstract We present Text2Room, a method for generating room-scale textured 3D meshes
from a given text prompt as input. To this end, we leverage pre-trained 2D text-to-image …

Text-guided diffusion models have revolutionized image and video generation and have
also been successfully used for optimization-based 3D object synthesis. Here we instead …

Despite the tremendous progress in neural radiance fields (NeRF), we still face a dilemma of
the trade-off between quality and efficiency, eg, MipNeRF presents fine-detailed and anti …

This paper presents DreamLLM, a learning framework that first achieves versatile
Multimodal Large Language Models (MLLMs) empowered with frequently overlooked …

Recent breakthroughs in text-to-4D generation rely on pre-trained text-to-image and text-to-
video models to generate dynamic 3D scenes. However current text-to-4D methods face a …

Implicit neural fields, typically encoded by a multilayer perceptron (MLP) that maps from
coordinates (eg, xyz) to signals (eg, signed distances), have shown remarkable promise as …