DeepSDF : Learning Continuous Signed Distance Functions for Shape Representation
計算機圖形學，3D計算機視覺和機器人技術社區已經提出了多種方法來表示3D幾何圖形以進行渲染和重構。 這些提供了在保真度，效率和壓縮能力之間的權衡。 在這項工作中，我們介紹了DeepSDF，這是一種學習到的連續形狀的符號距離函數（SDF）表示形式，可以實現高質量的形狀表示，部分和嘈雜的3D輸入數據的內插和完成。 DeepSDF和它的經典對應物一樣，通過連續的體積場表示形狀的表面：該點的大小表示到表
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相關文章
- 1. Kernel Functions for Machine Learning Applications
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