activity
20242026
collaborators

8 papers

cs.CV2026

MeshFlow: Efficient Artistic Mesh Generation via MeshVAE and Flow-based Diffusion Transformer

Weiyu Li, Antoine Toisoul, Tom Monnier +4

We present MeshFlow, a new method for generating artist-like 3D meshes. Current mesh generators often adopt Auto-Regressive (AR) next-token prediction, a natural choice given the d…

cs.GR2026

AssetGen: Deployable 3D Asset Generation at Interactive Speed

Dilin Wang, Xiaoyu Xiang, Kihyuk Sohn +14

While 3D generation is progressing rapidly, recent work has often focused on obtaining high-resolution assets, leaving user experience and deployability as afterthoughts. We presen…

cs.CV2026

MeshReGen: A Unified 3D Geometry Regeneration Framework

Geon Yeong Park, Roman Shapovalov, Rakesh Ranjan +3

We consider the problem of regenerating 3D objects from 2D images and initial 3D shapes. Most 3D generators operate in a one-shot fashion, converting text or images to a 3D object…

cs.CV2025

WorldGen: From Text to Traversable and Interactive 3D Worlds

Dilin Wang, Hyunyoung Jung, Tom Monnier +22

We introduce WorldGen, a system that enables the automatic creation of large-scale, interactive 3D worlds directly from text prompts. Our approach transforms natural language descr…

cs.CV2025

AutoPartGen: Autogressive 3D Part Generation and Discovery

Minghao Chen, Jianyuan Wang, Roman Shapovalov +6

We introduce AutoPartGen, a model that generates objects composed of 3D parts in an autoregressive manner. This model can take as input an image of an object, 2D masks of the objec…

cs.CV2025

Twinner: Shining Light on Digital Twins in a Few Snaps

Jesus Zarzar, Tom Monnier, Roman Shapovalov +2

We present the first large reconstruction model, Twinner, capable of recovering a scene's illumination as well as an object's geometry and material properties from only a few posed…