22 citations · 25 across the 8 of their papers we have counts for
11 papers
UltraTex: Unleashing 2K Multi-View Diffusion for 3D Texturing
Yibo Zhang, Ze Yuan, Nan Cao +4
High-quality texture generation is essential for creating realistic and production-ready 3D assets. Recent multi-view diffusion methods have shown promising results for image-guide…
Nexus: Native Mesh Generation with Diffusion
Hanxiao Wang, Ying-Tian Liu, Yuan-Chen Guo +5
Generating high-quality triangle meshes is essential for film, gaming, and interactive 3D applications. Mainstream methods rely on mesh serialization and autoregressive processes,…
Generative 3D Gaussians with Learned Density Control
Runjie Yan, Yan-Pei Cao, Peng Wang +2
We present Density-Sampled Gaussians (DeG), a novel 3D representation designed to bridge the gap between adaptive rendering primitives and scalable generative modeling. Unlike exis…
AniGen: Unified Fields for Animatable 3D Asset Generation
Yi-Hua Huang, Zi-Xin Zou, Yuting He +6
Animatable 3D assets, defined as geometry equipped with an articulated skeleton and skinning weights, are fundamental to interactive graphics, embodied agents, and animation produc…
LaFiTe: A Generative Latent Field for 3D Native Texturing
Chia-Hao Chen, Zi-Xin Zou, Yan-Pei Cao +6
Generating high-fidelity, seamless textures directly on 3D surfaces, what we term 3D-native texturing, remains a fundamental open challenge, with the potential to overcome long-sta…
SeqTex: Generate Mesh Textures in Video Sequence
Ze Yuan, Xin Yu, Yangtian Sun +4
Training native 3D texture generative models remains a fundamental yet challenging problem, largely due to the limited availability of large-scale, high-quality 3D texture datasets…
SparseFlex: High-Resolution and Arbitrary-Topology 3D Shape Modeling
Xianglong He, Zi-Xin Zou, Chia-Hao Chen +6
Creating high-fidelity 3D meshes with arbitrary topology, including open surfaces and complex interiors, remains a significant challenge. Existing implicit field methods often requ…
TripoSG: High-Fidelity 3D Shape Synthesis using Large-Scale Rectified Flow Models
Yangguang Li, Zi-Xin Zou, Zexiang Liu +8
Recent advancements in diffusion techniques have propelled image and video generation to unprecedented levels of quality, significantly accelerating the deployment and application…
TEXGen: a Generative Diffusion Model for Mesh Textures
Xin Yu, Ze Yuan, Yuan-Chen Guo +6
While high-quality texture maps are essential for realistic 3D asset rendering, few studies have explored learning directly in the texture space, especially on large-scale datasets…
DetailGen3D: Generative 3D Geometry Enhancement via Data-Dependent Flow
Ken Deng, Yuan-Chen Guo, Jingxiang Sun +6
Modern 3D generation methods can rapidly create shapes from sparse or single views, but their outputs often lack geometric detail due to computational constraints. We present Detai…
DreamCraft3D++: Efficient Hierarchical 3D Generation with Multi-Plane Reconstruction Model
Jingxiang Sun, Cheng Peng, Ruizhi Shao +6
We introduce DreamCraft3D++, an extension of DreamCraft3D that enables efficient high-quality generation of complex 3D assets. DreamCraft3D++ inherits the multi-stage generation pr…