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- W4387687228 abstract "Deformable linear objects are vastly represented in our everyday lives. It is often challenging even for humans to visually understand them, as the same object can be entangled so that it appears completely different. Examples of deformable linear objects include blood vessels and wiring harnesses, vital to the functioning of their corresponding systems, such as the human body and a vehicle. However, no point cloud datasets exist for studying 3D deformable linear objects. Therefore, we are introducing two point cloud datasets, PointWire and PointVessel. We evaluated state-of-the-art methods on the proposed large-scale 3D deformable linear object benchmarks. Finally, we analyzed the generalization capabilities of these methods by conducting transferability experiments on the PointWire and PointVessel datasets." @default.
- W4387687228 created "2023-10-17" @default.
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- W4387687228 date "2023-10-13" @default.
- W4387687228 modified "2023-10-18" @default.
- W4387687228 title "3D Understanding of Deformable Linear Objects: Datasets and Transferability Benchmark" @default.
- W4387687228 doi "https://doi.org/10.48550/arxiv.2310.08904" @default.
- W4387687228 hasPublicationYear "2023" @default.
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