collaborators

9 papers

cs.GR2026

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…

cs.GR2026

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…

cs.CV2026

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…

cs.CV2026

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…

cs.CV2025

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…

cs.CV2025

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…