3 papers
cs.CV2025
MoGe-2: Accurate Monocular Geometry with Metric Scale and Sharp Details
Ruicheng Wang, Sicheng Xu, Yue Dong +6
We propose MoGe-2, an advanced open-domain geometry estimation model that recovers a metric scale 3D point map of a scene from a single image. Our method builds upon the recent mon…
cs.CV2025
Structured 3D Latents for Scalable and Versatile 3D Generation
Jianfeng Xiang, Zelong Lv, Sicheng Xu +6
We introduce a novel 3D generation method for versatile and high-quality 3D asset creation. The cornerstone is a unified Structured LATent (SLAT) representation which allows decodi…
cs.CV2025
MoGe: Unlocking Accurate Monocular Geometry Estimation for Open-Domain Images with Optimal Training Supervision
Ruicheng Wang, Sicheng Xu, Cassie Dai +4
We present MoGe, a powerful model for recovering 3D geometry from monocular open-domain images. Given a single image, our model directly predicts a 3D point map of the captured sce…