<ul><li>The GARF (Generalizeable 3D reAssembly for Real-world Fractures) project focuses on using machine learning to precisely reassemble broken objects.</li><li>Traditional methods of reassembling objects from imperfect fragments are complex and time-consuming, while GARF utilizes synthetic data for training and successfully applies it to real-world objects.</li><li>GARF is a software framework that can handle highly complex breakage patterns in 3D scanned fragments, even with imperfect edges or missing pieces.</li><li>The GitHub repository for GARF includes the code and a demo is available for those interested.</li></ul>

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