Qitong Yang — accepted AI-conference papers

2026

Learning Hierarchical Hyperbolic Mixture Model for Part-aware 3D Generation

Qitong Yang, Mingtao Feng, Zijie Wu, Huixin Zhu, Weisheng Dong, Yaonan Wang +1

CVPR 2026

3D shape generation has become increasingly important for graphics and vision applications. Current part-aware 3D generation usually overlooks hierarchical part relations or inefficiently encodes multi-level semantics in Euclidean space. Thus we propose a novel framework for hierarchical and efficie

Cited by 0 Source ↗Scholar ↗

2025

Hierarchical Gaussian Mixture Model Splatting for Efficient and Part Controllable 3D Generation

Qitong Yang, Mingtao Feng, Zijie Wu, Weisheng Dong, Fangfang Wu, Yaonan Wang +1

CVPR 2025poster

3D content creation has achieved significant progress in terms of both quality and speed. Although current Gaussian Splatting-based methods can produce 3D objects within seconds, they are still limited by complex preprocessing or low controllability. In this paper, we introduce a novel framework des…

Cited by 0 Source ↗PDF ↗Scholar ↗