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5754 软件学报 2025 年第 36 卷第 12 期
[36] Fung S, Pan W, Liu X, Yearwood J, Dazeley R, Lu XQ. TopFormer: Topology-aware Transformer for point cloud registration. In: Proc.
of the 12th Int’l Conf. on Computational Visual Media. Wellington: Springer, 2024. 112–128. [doi: 10.1007/978-981-97-2095-8_7]
[37] Yu H, Hou J, Qin Z, Saleh M, Shugurov I, Wang K, Busam B, Ilic S. RIGA: Rotation-invariant and globally-aware descriptors for point
cloud registration. IEEE Trans. on Pattern Analysis and Machine Intelligence, 2024, 46(5): 3796–3812. [doi: 10.1109/TPAMI.2023.
3349199]
[38] Li JW, Zhan JW. Review on 3D point cloud registration method. Journal of Image and Graphics, 2022, 27(2): 349–367 (in Chinese with
English abstract). [doi: 10.11834/jig.210243]
[39] Wang Y, Sun YB, Liu ZW, Sarma SE, Bronstein MM, Solomon JM. Dynamic graph CNN for learning on point clouds. ACM Trans. on
Graphics, 2019, 38(5): 146. [doi: 10.1145/3326362]
[40] Wu ZR, Song SR, Khosla A, Yu F, Zhang LG, Tang XO, Xiao JX. 3D ShapeNets: A deep representation for volumetric shapes. In: Proc.
of the 2015 IEEE Conf. on Computer Vision and Pattern Recognition. Boston: IEEE, 2015. 1912–1920. [doi: 10.1109/CVPR.2015.
7298801]
[41] Yi L, Kim VG, Ceylan D, Shen IC, Yan MY, Su H, Lu CW, Huang QX, Sheffer A, Guibas L. A scalable active framework for region
annotation in 3D shape collections. ACM Trans. on Graphics, 2016, 35(6): 210. [doi: 10.1145/2980179.2980238]
[42] Bogo F, Romero J, Loper M, Black MJ. FAUST: Dataset and evaluation for 3D mesh registration. In: Proc. of the 2014 IEEE Conf. on
Computer Vision and Pattern Recognition. Columbus: IEEE, 2014. 3794–3801. [doi: 10.1109/CVPR.2014.491]
[43] Hezroni I, Drory A, Giryes R, Avidan S. DeepBBS: Deep best buddies for point cloud registration. In: Proc. of the 2021 Int’l Conf. on 3D
Vision. London: IEEE, 2021. 342–351. [doi: 10.1109/3DV53792.2021.00044]
[44] Cao FL, Wang LP, Ye HL. SharpGConv: A novel graph method with plug-and-play sharpening convolution for point cloud registration.
IEEE Trans. on Circuits and Systems for Video Technology, 2024, 34(8): 7095–7105. [doi: 10.1109/TCSVT.2024.3369468]
附中文参考文献:
[38] 李建微, 占家旺. 三维点云配准方法研究进展. 中国图象图形学报, 2022, 27(2): 349–367. [doi: 10.11834/jig.210243]
邱巧燕(1999-), 女, 硕士生, 主要研究领域为深 曹飞龙(1965-), 男, 博士, 教授, 博士生导师, 主
度学习, 点云分析. 要研究领域为深度学习, 点云分析.
叶海良(1990-), 男, 博士, 副教授, CCF 专业会 吕科(1971-), 男, 博士, 教授, 博士生导师, CCF
员, 主要研究领域为深度学习, 点云分析. 专业会员, 主要研究领域为计算机视觉, 计算机
图形学.

