2026-01-16

ShapeR: Robust Conditional 3D Shape Generation from Casual Captures

Yawar Siddiqui, Duncan Frost, Samir Aroudj, Armen Avetisyan, Henry Howard-Jenkins, Daniel DeTone, Pierre Moulon, Qirui Wu, Zhengqin Li, Julian Straub, Richard Newcombe, Jakob Engel

Arxiv 01/2026 project page github video weights

ShapeR generates high-fidelity 3D shapes from casually captured image sequences. It uses SLAM, 3D detection, and vision-language models to extract per-object conditioning and a rectified flow transformer to generate shapes, achieving 2.7x improvement in Chamfer distance over state of the art.