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【论文阅读-室内场景合成：交互度量】Human-centric metrics for indoor scene assessment and synthesis
【关键词】3D modeling、Environment assessment、Indoor scene synthesis 【主要问题】对于已知类型的房间（已知摆放物品、已知房间形状、门窗位置）布局 【主要思想】定义以人为中心的度量来定量评估布局的质量（Human-Centric Metrics） 【主要方法】 定量评估方法 Human-object facScanNet: Richly-annotated 3D Reconstructions of Indoor Scenes摘要和简介翻译
ScanNet: Richly-annotated 3D Reconstructions of Indoor Scenes ScanNet: 大量标注的室内场景三维重建 Abstract 摘要 A key requirement for leveraging supervised deep learning methods Is the availability of large, labeled datasets. Unfortunately, in th论文笔记：GEOMETRIC CONTEXT AND ORIENTATION MAP COMBINATION FOR INDOOR CORRIDOR MODELING USING A SINGLE I
GEOMETRIC CONTEXT AND ORIENTATION MAP COMBINATION FOR INDOOR CORRIDOR MODELING USING A SINGLE IMAGE(ISPRS 2016) 传统方法恢复房间布局，本文侧重对走廊图片进行布局恢复，主要分以下步骤：消失点估计，基于消失点的布局生成，布局评分(结合方向图OM和几何上下文GC) Vanishinmybatis 父子关系递归查询，父子菜单
<!--级联查询返回模型--> <resultMap type="Map" id="fatherMap"> <id column="id" property="id"/> <collection property="list" ofType="com.jmxf.entity.zdbwManage.ZdbwIndoorubuntu NGINX uwsgi https 部署Django 遇到的问题
搞了3天终于把Django成功部署到Ubuntu，记录一下； 引用来自泡泡茶壶： Ubuntu下的Nginx + Uwsgi + Django项目部署详细流程 前提说明： Django作为小程序的后端，因小程序的请求到后端的都是https请求，所以Django必须支持https请求 写在前面： 部署Django项目前，先用Django自带服务器运行一下看Indoor Signal Focusing with Deep Learning Designed Reconfigurable Intelligent Surfaces
Indoor Signal Focusing with Deep Learning Designed Reconfigurable Intelligent Surfaces Chongwen Huang1 , George C. Alexandropoulos2 , Chau Yuen1 , and Merouane Debbah ´ 3,4 1Singapore University of Technology and Design, 487372 Singapore Phrases compri