SplineGen: a generative model for B-spline approximation of unorganized points
<|reference_start|>SplineGen: a generative model for B-spline approximation of unorganized points: This paper presents a learning-based method to solve the traditional parameterization and knot placement problems in B-spline approximation. Different from conventional heuristic methods or recent AI-based methods, the proposed method does not assume ordered or fixed-size data points as input. There is also no need for manually setting the number of knots. It casts the parameterization and knot placement problems as a sequence-to-sequence translation problem, a generative process automatically determining the number of knots, their placement, parameter values, and their ordering. Once trained, SplineGen demonstrates a notable improvement over existing methods, with a one to two orders of magnitude increase in approximation accuracy on test data.<|reference_end|>
@article{zou2024splinegen:,
    title={SplineGen: a generative model for B-spline approximation of unorganized
  points},
    author={Qiang Zou, Lizhen Zhu},
    journal={arXiv preprint arXiv:2406.09692},
    year={2024},
    archivePrefix={arXiv},
    eprint={2406.09692},
    primaryClass={cs.CE cs.CG}
}