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                    Haocheng Wan    
                        万昊承      
                    
                   
                  I am a Master's student at University College London and received my Bachelor's degree from Hangzhou Dianzi University. 
				   I have wide research interests in 3D vision and deep learning.
                   
                  
                    Email  / 
                    
                    
                    Google Scholar  / 
                    
                    Github
                   
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                  Publication ( * indicates equal contributions in alphabetical order)
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                    PatchFormer: An Efficient Point Transformer with Patch Attention
                  
                   
				  Cheng Zhang*, Haocheng Wan*, Xinyi Shen, Zizhao Wu
                   
                                IEEE/CVF Conference on Computer Vision and Pattern Recognition(CVPR), 2022
                   
                   
                  We propose a new type of attention mechanism and a lightweight block with multiscale features.
                   
                  [paper][code]
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                    PVT: Point-Voxel Transformer for 3D Deep Learning
                  
                   
                  Cheng Zhang*, Haocheng Wan*, Shengqiang Liu, Xinyi Shen, Zizhao Wu
                   
                                International Journal of Intelligent Systems, 2022
                   
                   
                  We present a pure-transformer backbone architecture for 3D deep learning with high performance and efficiency.
                   
                  [paper]
				  [code]
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                    Graph-PBN: Graph-based Parallel Branch Network for Efficient Point Cloud Learning
                  
                   
                  Cheng Zhang, Hao Chen, Haocheng Wan, Ping Yang, Zizhao Wu
                   
                                Graphical Models, Volume 119, 2022, 101120
                   
                   
                  We introduce a novel parallel branch structure for 3D deep learning. A new convolution operator were designed for local graph-based networks
                   
                  [paper]
				  [code]
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