5 papers
Arko-T: A Foundation Model for Text-to-Structured 3D Generation
Liang Wang, Zhaoyang Xi, Zekai Xiang +5
Text-to-3D systems can now synthesize a model from a single sentence, yet the result is a shape to render, not a design to edit. We present Arko-T, a 4B-parameter text-to-design mo…
Text2CAD-Bench: A Benchmark for LLM-based Text-to-Parametric CAD Generation
Liang Wang, Heng Meng, Zekai Xiang +4
Text-to-CAD generation aims to create parametric CAD models from natural language, enabling rapid prototyping and intuitive design workflows. However, existing benchmarks focus on…
Text2VDM: Text to Vector Displacement Maps for Expressive and Interactive 3D Sculpting
Hengyu Meng, Duotun Wang, Zhijing Shao +2
Professional 3D asset creation often requires diverse sculpting brushes to add surface details and geometric structures. Despite recent progress in 3D generation, producing reusabl…
HeadEvolver: Text to Head Avatars via Expressive and Attribute-Preserving Mesh Deformation
Duotun Wang, Hengyu Meng, Zeyu Cai +6
Current text-to-avatar methods often rely on implicit representations (e.g., NeRF, SDF, and DMTet), leading to 3D content that artists cannot easily edit and animate in graphics so…
DEGAS: Detailed Expressions on Full-Body Gaussian Avatars
Zhijing Shao, Duotun Wang, Qing-Yao Tian +7
Although neural rendering has made significant advances in creating lifelike, animatable full-body and head avatars, incorporating detailed expressions into full-body avatars remai…