most citedWonder3D++: Cross-domain Diffusion for High-fidelity 3D Generation from a Single Image

2 citations · 2 across the 6 of their papers we have counts for

collaborators

8 papers

cs.CV2025

EchoMotion: Unified Human Video and Motion Generation via Dual-Modality Diffusion Transformer

Yuxiao Yang, Hualian Sheng, Sijia Cai +6

Video generation models have advanced significantly, yet they still struggle to synthesize complex human movements due to the high degrees of freedom in human articulation. This li…

cs.CV20252 cited

Wonder3D++: Cross-domain Diffusion for High-fidelity 3D Generation from a Single Image

Yuxiao Yang, Xiao-Xiao Long, Zhiyang Dou +7

In this work, we introduce \textbf{Wonder3D++}, a novel method for efficiently generating high-fidelity textured meshes from single-view images. Recent methods based on Score Disti…

cs.CV2025

Target-Balanced Score Distillation

Zhou Xu, Qi Wang, Yuxiao Yang +3

Score Distillation Sampling (SDS) enables 3D asset generation by distilling priors from pretrained 2D text-to-image diffusion models, but vanilla SDS suffers from over-saturation a…

cs.CV2025

Auto-Regressively Generating Multi-View Consistent Images

JiaKui Hu, Yuxiao Yang, Jialun Liu +3

Generating multi-view images from human instructions is crucial for 3D content creation. The primary challenges involve maintaining consistency across multiple views and effectivel…

cs.HC2025

SimVecVis: A Dataset for Enhancing MLLMs in Visualization Understanding

Can Liu, Chunlin Da, Xiaoxiao Long +3

Current multimodal large language models (MLLMs), while effective in natural image understanding, struggle with visualization understanding due to their inability to decode the dat…

cs.CV2025

NOVA3D: Normal Aligned Video Diffusion Model for Single Image to 3D Generation

Yuxiao Yang, Peihao Li, Yuhong Zhang +5

3D AI-generated content (AIGC) has made it increasingly accessible for anyone to become a 3D content creator. While recent methods leverage Score Distillation Sampling to distill 3…