collaborators

12 papers

cs.CV2026

Mesh BDF: Barycentric Dominance Field for 3D Native Mesh Generation

Gaochao Song, Haohan Weng, Luo Zhang +2

Autoregressive (AR) modeling has recently achieved remarkable progress in native 3D mesh generation, largely due to its natural ability to handle variable-length, discrete data str…

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.CV2026

Hunyuan3D 2.0: Scaling Diffusion Models for High Resolution Textured 3D Assets Generation

Zibo Zhao, Zeqiang Lai, Qingxiang Lin +71

We present Hunyuan3D 2.0, an advanced large-scale 3D synthesis system for generating high-resolution textured 3D assets. This system includes two foundation components: a large-sca…

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

Topology-Preserved Auto-regressive Mesh Generation in the Manner of Weaving Silk

Gaochao Song, Zibo Zhao, Haohan Weng +3

Existing auto-regressive mesh generation approaches suffer from ineffective topology preservation, which is crucial for practical applications. This limitation stems from previous…

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…