𝗗𝗮𝘆-𝟭𝟱𝟰 Computer Vision Learning 𝗣𝗙-𝗡𝗲𝘁: : Point Fractal Network for 3D Point Cloud Completion by Shanghai Jiao Tong University and Sense Time Research Follow me for similar post : @🇮🇳 Ashish Patel Interesting Facts : 🔸 This is a paper in CVPR 2020 with over 39 citations. 🔸 It Outperforms with the LGAN-AE, 3D-Capsule etc. ------------------------------------------------------------------- 𝗔𝗺𝗮𝘇𝗶𝗻𝗴 𝗥𝗲𝘀𝗲𝗮𝗿𝗰𝗵 : https://lnkd.in/ecjC7-G code : https://lnkd.in/eACTpaE ------------------------------------------------------------------- 𝗜𝗠𝗣𝗢𝗥𝗧𝗔𝗡𝗖𝗘 🔸 A point cloud fractal network (PF-Net: Point Fractal Network) is proposed, which uses an idea similar to fractal geometry. It also takes an incomplete point cloud as input, but only outputs the missing part of the point cloud, and better retains the information of an object. Individual characteristics. 🔸 Compared with other networks, PF-Net's patching has the following advantages: (1) It retains the unique geometric characteristics of the input point cloud; (2) The detailed features are richer and softer; (3) The overall quality of the generated point cloud is higher. #computervision #artificialintelligence #innovation
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