10 papers
PolyFlow: Continuous Topology Embedding Flow Matching for Artist-style Mesh Generation
Chunshi Wang, Haohan Weng, Junliang Ye +9
Autoregressive Transformers dominate high-quality mesh generation by producing artist-worthy topologies, yet their inherent sequential decoding induces substantial computational ov…
MeshFIM: Local Low-Poly Mesh Editing via Fill-in-the-Middle Autoregressive Generation
Dingdong Yang, Jian Liu, Biwen Lei +6
Autoregressive (AR) models can generate high-quality low-poly meshes from point clouds, but they still operate in an all-or-nothing manner: when a local region is unsatisfactory, t…
Mesh-Pro: Asynchronous Advantage-guided Ranking Preference Optimization for Artist-style Quadrilateral Mesh Generation
Zhen Zhou, Jian Liu, Biwen Lei +10
Reinforcement learning (RL) has demonstrated remarkable success in text and image generation, yet its potential in 3D generation remains largely unexplored. Existing attempts typic…
QuadGPT: Native Quadrilateral Mesh Generation with Autoregressive Models
Jian Liu, Chunshi Wang, Song Guo +9
The generation of quadrilateral-dominant meshes is a cornerstone of professional 3D content creation. However, existing generative models generate quad meshes by first generating t…
Auto-Regressive Surface Cutting
Yang Li, Victor Cheung, Xinhai Liu +8
Surface cutting is a fundamental task in computer graphics, with applications in UV parameterization, texture mapping, and mesh decomposition. However, existing methods often produ…
Auto-Connect: Connectivity-Preserving RigFormer with Direct Preference Optimization
Jingfeng Guo, Jian Liu, Jinnan Chen +9
We introduce Auto-Connect, a novel approach for automatic rigging that explicitly preserves skeletal connectivity through a connectivity-preserving tokenization scheme. Unlike prev…
FreeMesh: Boosting Mesh Generation with Coordinates Merging
Jian Liu, Haohan Weng, Biwen Lei +6
The next-coordinate prediction paradigm has emerged as the de facto standard in current auto-regressive mesh generation methods. Despite their effectiveness, there is no efficient…
Mesh-RFT: Enhancing Mesh Generation via Fine-grained Reinforcement Fine-Tuning
Jian Liu, Jing Xu, Song Guo +10
Existing pretrained models for 3D mesh generation often suffer from data biases and produce low-quality results, while global reinforcement learning (RL) methods rely on object-lev…
Scaling Mesh Generation via Compressive Tokenization
Haohan Weng, Zibo Zhao, Biwen Lei +10
We propose a compressive yet effective mesh representation, Blocked and Patchified Tokenization (BPT), facilitating the generation of meshes exceeding 8k faces. BPT compresses mesh…
Hunyuan3D 1.0: A Unified Framework for Text-to-3D and Image-to-3D Generation
Xianghui Yang, Huiwen Shi, Bowen Zhang +20
While 3D generative models have greatly improved artists' workflows, the existing diffusion models for 3D generation suffer from slow generation and poor generalization. To address…