正确性
计算机科学
像素
多边形网格
编码(集合论)
集合(抽象数据类型)
解析
人工智能
功能(生物学)
算法
计算机视觉
理论计算机科学
计算机图形学(图像)
程序设计语言
进化生物学
生物
作者
Kennard Yanting Chan,Guosheng Lin,Haiyu Zhao,Weisi Lin
出处
期刊:Cornell University - arXiv
日期:2022-01-01
标识
DOI:10.48550/arxiv.2211.07955
摘要
We propose IntegratedPIFu, a new pixel aligned implicit model that builds on the foundation set by PIFuHD. IntegratedPIFu shows how depth and human parsing information can be predicted and capitalised upon in a pixel-aligned implicit model. In addition, IntegratedPIFu introduces depth oriented sampling, a novel training scheme that improve any pixel aligned implicit model ability to reconstruct important human features without noisy artefacts. Lastly, IntegratedPIFu presents a new architecture that, despite using less model parameters than PIFuHD, is able to improves the structural correctness of reconstructed meshes. Our results show that IntegratedPIFu significantly outperforms existing state of the arts methods on single view human reconstruction. Our code has been made available online.
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