3 citations · 4 across the 3 of their papers we have counts for
5 papers
TaoFlowForge: Progressive Native Mesh Generation via Cascaded Flow Matching
Xianze Fang, Qiyuan Feng, Dongfang Sun +6
3D content generation technology has significantly advanced the work of designers, as well as the 3D printing and gaming industries. However, it remains difficult to produce lightw…
GeoDiff3D: Self-Supervised 3D Scene Generation with Geometry-Constrained 2D Diffusion Guidance
Haozhi Zhu, Miaomiao Zhao, Dingyao Liu +4
3D scene generation is a core technology for gaming, film/VFX, and VR/AR. Growing demand for rapid iteration, high-fidelity detail, and accessible content creation has further incr…
CAGE-GS: High-fidelity Cage Based 3D Gaussian Splatting Deformation
Yifei Tong, Runze Tian, Xiao Han +3
As 3D Gaussian Splatting (3DGS) gains popularity as a 3D representation of real scenes, enabling user-friendly deformation to create novel scenes while preserving fine details from…
ARAP-GS: Drag-driven As-Rigid-As-Possible 3D Gaussian Splatting Editing with Diffusion Prior
Xiao Han, Runze Tian, Yifei Tong +3
Drag-driven editing has become popular among designers for its ability to modify complex geometric structures through simple and intuitive manipulation, allowing users to adjust an…
GSEditPro: 3D Gaussian Splatting Editing with Attention-based Progressive Localization
Yanhao Sun, RunZe Tian, Xiao Han +3
With the emergence of large-scale Text-to-Image(T2I) models and implicit 3D representations like Neural Radiance Fields (NeRF), many text-driven generative editing methods based on…