2 citations · 6 across the 10 of their papers we have counts for
11 papers
ArtLLM: Generating Articulated Assets via 3D LLM
Penghao Wang, Siyuan Xie, Hongyu Yan +4
Creating interactive digital environments for gaming, robotics, and simulation relies on articulated 3D objects whose functionality emerges from their part geometry and kinematic s…
HY3D-Bench: Generation of 3D Assets
Team Hunyuan3D, :, Bowen Zhang +22
While recent advances in neural representations and generative models have revolutionized 3D content creation, the field remains constrained by significant data processing bottlene…
LATTICE: Democratize High-Fidelity 3D Generation at Scale
Zeqiang Lai, Yunfei Zhao, Zibo Zhao +5
We present LATTICE, a new framework for high-fidelity 3D asset generation that bridges the quality and scalability gap between 3D and 2D generative models. While 2D image synthesis…
NaTex: Seamless Texture Generation as Latent Color Diffusion
Zeqiang Lai, Yunfei Zhao, Zibo Zhao +5
We present NaTex, a native texture generation framework that predicts texture color directly in 3D space. In contrast to previous approaches that rely on baking 2D multi-view image…
Hunyuan3D-Omni: A Unified Framework for Controllable Generation of 3D Assets
Team Hunyuan3D, :, Bowen Zhang +17
Recent advances in 3D-native generative models have accelerated asset creation for games, film, and design. However, most methods still rely primarily on image or text conditioning…
SVG-Head: Hybrid Surface-Volumetric Gaussians for High-Fidelity Head Reconstruction and Real-Time Editing
Heyi Sun, Cong Wang, Tian-Xing Xu +4
Creating high-fidelity and editable head avatars is a pivotal challenge in computer vision and graphics, boosting many AR/VR applications. While recent advancements have achieved p…