SHREC’22 track: Open-Set 3D Object Retrieval

Author:

Feng Yifan,Gao Yue,Zhao Xibin,Guo Yandong,Bagewadi Nihar,Bui Nhat-Tan,Dao Hieu,Gangisetty Shankar,Guan Ripeng,Han Xie,Hua Cong,Hunakunti Chidambar,Jiang Yu,Jiao Shichao,Ke Yuqi,Kuang Liqun,Liu Anan,Nguyen Dinh-Huan,Nguyen Hai-Dang,Nie Weizhi,Pham Bang-Dang,Raikar Karthik,Tang Qingmei,Tran Minh-Triet,Wan Jialong,Yan Chenggang,You Haoxuan,Zhu Difei

Publisher

Elsevier BV

Subject

Computer Graphics and Computer-Aided Design,Human-Computer Interaction,General Engineering

Reference29 articles.

1. Feng Y, Feng Y, You H, Zhao X, Gao Y. Meshnet: Mesh neural network for 3d shape representation. In: Proceedings of the AAAI conference on artificial intelligence, Vol. 33; 2019, pp. 8279–86.

2. Meshcnn: a network with an edge;Hanocka;ACM Trans Graph,2019

3. Subdivision-based mesh convolution networks;Hu;ACM Trans Graph,2022

4. Qi CR, Su H, Mo K, Guibas LJ. Pointnet: Deep learning on point sets for 3d classification and segmentation. In: Proceedings of the IEEE conference on computer vision and pattern recognition; 2017, pp. 652–60.

5. Pointnet++: Deep hierarchical feature learning on point sets in a metric space;Qi;Adv Neural Inf Process Syst,2017

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