5 papers
LSRM: High-Fidelity Object-Centric Reconstruction via Scaled Context Windows
Zhengqin Li, Cheng Zhang, Jakob Engel +1
We introduce the Large Sparse Reconstruction Model to study how scaling transformer context windows affects feed-forward 3D reconstruction. Although recent object-centric feed-forw…
ART: Articulated Reconstruction Transformer
Zizhang Li, Cheng Zhang, Zhengqin Li +7
We introduce ART, Articulated Reconstruction Transformer -- a category-agnostic, feed-forward model that reconstructs complete 3D articulated objects from only sparse, multi-state…
CalibAnyView: Beyond Single-View Camera Calibration in the Wild
Boying Li, Cheng Zhang, Weirong Chen +5
Camera calibration is fundamental to reliable geometric perception, yet classical approaches rely on dedicated targets, successful reconstruction, or dense view coverage, which cas…
Digital Twin Catalog: A Large-Scale Photorealistic 3D Object Digital Twin Dataset
Zhao Dong, Ka Chen, Zhaoyang Lv +14
We introduce the Digital Twin Catalog (DTC), a new large-scale photorealistic 3D object digital twin dataset. A digital twin of a 3D object is a highly detailed, virtually indistin…
LIRM: Large Inverse Rendering Model for Progressive Reconstruction of Shape, Materials and View-dependent Radiance Fields
Zhengqin Li, Dilin Wang, Ka Chen +11
We present Large Inverse Rendering Model (LIRM), a transformer architecture that jointly reconstructs high-quality shape, materials, and radiance fields with view-dependent effects…