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  • Sawada T and Katsurai M. MambaPainter: Neural Stroke-Based Rendering in a Single Step. SIGGRAPH Asia 2024 Posters. (1-2).

    https://doi.org/10.1145/3681756.3697906

  • Song Y, Huang S, Yao C, Ci H, Ye X, Liu J, Zhang Y and Shou M. ProcessPainter: Learning to draw from sequence data. SIGGRAPH Asia 2024 Conference Papers. (1-10).

    https://doi.org/10.1145/3680528.3687596

  • Chen B, Wang Y, Curless B, Kemelmacher-Shlizerman I and Seitz S. Inverse Painting: Reconstructing The Painting Process. SIGGRAPH Asia 2024 Conference Papers. (1-11).

    https://doi.org/10.1145/3680528.3687574

  • Hu Z, Chen Y, Zhao Z, Liu J, Ke B and Ni B. Towards Artist-Like Painting Agents with Multi-Granularity Semantic Alignment. Proceedings of the 32nd ACM International Conference on Multimedia. (10191-10199).

    https://doi.org/10.1145/3664647.3681245

  • Qiu J, Lu P, Peng X, Guo W, Zhao Z and Dong X. Learning Realistic Sketching: A Dual-agent Reinforcement Learning Approach. Proceedings of the 32nd ACM International Conference on Multimedia. (5921-5929).

    https://doi.org/10.1145/3664647.3680759

  • Hu T, Yi R, Qian B, Zhang J, Rosin P and Lai Y. (2024). SuperSVG: Superpixel-Based Scalable Vector Graphics Synthesis 2024 IEEE/CVF Conference on Computer Vision and Pattern Recognition (CVPR). 10.1109/CVPR52733.2024.02351. 979-8-3503-5300-6. (24892-24901).

    https://ieeexplore.ieee.org/document/10658241/

  • Zhu H, Ian Chong J, Hu T, Yi R, Lai Y and Rosin P. (2024). SAMVG: A Multi-Stage Image Vectorization Model with the Segment-Anything Model ICASSP 2024 - 2024 IEEE International Conference on Acoustics, Speech and Signal Processing (ICASSP). 10.1109/ICASSP48485.2024.10447396. 979-8-3503-4485-1. (4350-4354).

    https://ieeexplore.ieee.org/document/10447396/

  • TANG B, HU T, DU Y, YI R and MA L. (2024). Curved-stroke-based neural painting and stylization through thin plate spline interpolation. SCIENTIA SINICA Informationis. 10.1360/SSI-2023-0194. 54:2. (301). Online publication date: 1-Feb-2024.

    https://engine.scichina.com/doi/10.1360/SSI-2023-0194

  • Su X and Kim H. Automatic Stylized Action Generation in Animation Using Deep Learning. IEEE Access. 10.1109/ACCESS.2024.3486024. 12. (188773-188786).

    https://ieeexplore.ieee.org/document/10734093/