Despite the remarkable performance of score distillation in text-to-3D generation such
techniques notoriously suffer from view inconsistency issues also known as" Janus" artifact …

Recent years have seen an explosion of work and interest in text‐to‐3D shape generation.
Much of the progress is driven by advances in 3D representations, large‐scale pretraining …

As a dominant force in text-to-image generation tasks, Diffusion Probabilistic Models (DPMs)
face a critical challenge in controllability, struggling to adhere strictly to complex, multi …

We present Envision3D, a novel method for efficiently generating high-quality 3D content
from a single image. Recent methods that extract 3D content from multi-view images …

Text-to-3D content creation has recently received much attention, especially with the
prevalence of 3D Gaussians Splatting. In general, GS-based methods comprise two key …

Recent advancements in diffusion models have led to significant improvements in the
generation and animation of 4D full-body human-object interactions (HOI). Nevertheless …

Current 3D content generation builds on generative models that output RGB images.
Modern graphics pipelines, however, require physically-based rendering (PBR) material …

Recently, text-to-3D generation has attracted significant attention, resulting in notable
performance enhancements. Previous methods utilize end-to-end 3D generation models to …

While 2D diffusion models generate realistic, high-detail images, 3D shape generation
methods like Score Distillation Sampling (SDS) built on these 2D diffusion models produce …

3D modeling has long been an important area in computer vision and computer graphics.
Recently, thanks to the breakthroughs in neural representations and generative models, we …