Transfer Learning from Synthetic to Real LiDAR Point Cloud for Semantic Segmentation | Zendy

Aoran Xiao | Zendy; Jiaxing Huang | Zendy; Dayan Guan | Zendy; Fangneng Zhan | Zendy; Shijian Lu | Zendy

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Transfer Learning from Synthetic to Real LiDAR Point Cloud for Semantic Segmentation

Author(s) -

Aoran Xiao,

Jiaxing Huang,

Dayan Guan,

Fangneng Zhan,

Shijian Lu

Publication year - 2022

Publication title -

proceedings of the aaai conference on artificial intelligence

Language(s) - English

Resource type - Journals

eISSN - 2374-3468

pISSN - 2159-5399

DOI - 10.1609/aaai.v36i3.20183

Subject(s) - point cloud , computer science , segmentation , transfer of learning , lidar , synthetic data , artificial intelligence , point (geometry) , adaptation (eye) , domain (mathematical analysis) , component (thermodynamics) , annotation , translation (biology) , scale (ratio) , domain adaptation , data mining , pattern recognition (psychology) , remote sensing , geometry , mathematics , mathematical analysis , biochemistry , chemistry , physics , quantum mechanics , messenger rna , gene , classifier (uml) , optics , thermodynamics , geology

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