3 citations · 3 across the 4 of their papers we have counts for
8 papers
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…
ShapeGen: Towards High-Quality 3D Shape Synthesis
Yangguang Li, Xianglong He, Zi-Xin Zou +4
Inspired by generative paradigms in image and video, 3D shape generation has made notable progress, enabling the rapid synthesis of high-fidelity 3D assets from a single image. How…
OmniPart: Part-Aware 3D Generation with Semantic Decoupling and Structural Cohesion
Yunhan Yang, Yufan Zhou, Yuan-Chen Guo +7
The creation of 3D assets with explicit, editable part structures is crucial for advancing interactive applications, yet most generative methods produce only monolithic shapes, lim…
HoloPart: Generative 3D Part Amodal Segmentation
Yunhan Yang, Yuan-Chen Guo, Yukun Huang +5
3D part amodal segmentation--decomposing a 3D shape into complete, semantically meaningful parts, even when occluded--is a challenging but crucial task for 3D content creation and…
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…