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Radu Iovita

3 accepted papers

2026

CRAG: Can 3D Generative Models Help 3D Assembly?

ICML 2026poster

Most existing 3D assembly methods treat the problem as pure pose estimation, rearranging observed parts via rigid transformations. In contrast, human assembly naturally couples structural reasoning with holistic shape inference. Inspired by this intuition, we reformulate 3D assembly as a joint probl…

Cited by 0SourceScholar
2025

GARF: Learning Generalizable 3D Reassembly for Real-World Fractures

ICCV 2025poster

3D reassembly is a challenging spatial intelligence task with broad applications across scientific domains. While large-scale synthetic datasets have fueled promising learning-based approaches, their generalizability to different domains is limited. Critically, it remains uncertain whether models tr…

Cited by 0SourcePDFScholar
2024

LUWA Dataset: Learning Lithic Use-Wear Analysis on Microscopic Images

CVPR 2024highlight

Lithic Use-Wear Analysis (LUWA) using microscopic images is an underexplored vision-for-science research area. It seeks to distinguish the worked material which is critical for understanding archaeological artifacts material interactions tool functionalities and dental records. However this challeng…

Cited by 4SourcePDFScholar