4 citations · 4 across the 2 of their papers we have counts for
3 papers
cs.CV2026
CRAG: Can 3D Generative Models Help 3D Assembly?
Zeyu Jiang, Sihang Li, Siqi Tan +8
Most existing 3D assembly methods treat the problem as pure pose estimation, rearranging observed parts via rigid transformations. In contrast, human assembly naturally couples str…
cs.CV2025
GARF: Learning Generalizable 3D Reassembly for Real-World Fractures
Sihang Li, Zeyu Jiang, Grace Chen +9
3D reassembly is a challenging spatial intelligence task with broad applications across scientific domains. While large-scale synthetic datasets have fueled promising learning-base…
cs.CV2024★ 4 cited
LUWA Dataset: Learning Lithic Use-Wear Analysis on Microscopic Images
Jing Zhang, Irving Fang, Juexiao Zhang +7
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 un…