12 citations · 12 across the 2 of their papers we have counts for
4 papers
MeshCraft: Exploring Efficient and Controllable Mesh Generation with Flow-based DiTs
Xianglong He, Junyi Chen, Di Huang +5
In the domain of 3D content creation, achieving optimal mesh topology through AI models has long been a pursuit for 3D artists. Previous methods, such as MeshGPT, have explored the…
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…
GVGEN: Text-to-3D Generation with Volumetric Representation
Xianglong He, Junyi Chen, Sida Peng +6
In recent years, 3D Gaussian splatting has emerged as a powerful technique for 3D reconstruction and generation, known for its fast and high-quality rendering capabilities. To addr…
Convolution Meets LoRA: Parameter Efficient Finetuning for Segment Anything Model
Zihan Zhong, Zhiqiang Tang, Tong He +2
The Segment Anything Model (SAM) stands as a foundational framework for image segmentation. While it exhibits remarkable zero-shot generalization in typical scenarios, its advantag…