The emergence of 3D Gaussian splatting (3DGS) has greatly accelerated rendering in novel
view synthesis. Unlike neural implicit representations like neural radiance fields (NeRFs) …

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 …

Abstract We present Visual AutoRegressive modeling (VAR), a new generation paradigm
that redefines the autoregressive learning on images as coarse-to-fine" next-scale …

This work aims to learn a high-quality text-to-video (T2V) generative model by leveraging a
pre-trained text-to-image (T2I) model as a basis. It is a highly desirable yet challenging task …

Large language models (LLMs) are fine-tuned using human comparison data with
Reinforcement Learning from Human Feedback (RLHF) methods to make them better …

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 …

Diffusion models have achieved great success in synthesizing high-quality images.
However generating high-resolution images with diffusion models is still challenging due to …

Instruction-based image editing holds immense potential for a variety of applications as it
enables users to perform any editing operation using a natural language instruction …

Diffusion models are the main driver of progress in image and video synthesis, but suffer
from slow inference speed. Distillation methods, like the recently introduced adversarial …

World models can foresee the outcomes of different actions, which is of paramount
importance for autonomous driving. Nevertheless, existing driving world models still have …