79 lines
13 KiB
Markdown
79 lines
13 KiB
Markdown
---
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title: 未命名
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date: 2023-12-29 16:20:43
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excerpt:
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tags:
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rating: ⭐
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---
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# 前言
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- 文档:https://sibr.gitlabpages.inria.fr
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- 代码:https://gitlab.inria.fr/sibr/sibr_core
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- 案例代码
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- [renderer/SimpleView.hpp](https://gitlab.inria.fr/mbenadel/sibr_simple/-/blob/master/renderer/SimpleView.hpp)&[renderer/SimpleView.cpp](https://gitlab.inria.fr/mbenadel/sibr_simple/-/blob/master/renderer/SimpleView.cpp)
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- [renderer/SimpleRenderer.hpp](https://gitlab.inria.fr/mbenadel/sibr_simple/-/blob/master/renderer/SimpleRenderer.hpp)&[renderer/SimpleRenderer.cpp](https://gitlab.inria.fr/mbenadel/sibr_simple/-/blob/master/renderer/SimpleRenderer.cpp)
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- [Simple SIBR Project](https://gitlab.inria.fr/sibr/projects/simple)
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- [SIBR/OptiX integration example](https://sibr.gitlabpages.inria.fr/docs/0.9.6/optixPage.html)
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- [Tensorflow/OpenGL Interop for SIBR](https://sibr.gitlabpages.inria.fr/docs/0.9.6/tfgl_interopPage.html)
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- Shader:需要将你自己编写的Shader放入**renderer/shaders**文件夹中
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- 关键词:
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- Structure-from-Motion (SfM)
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- Multi-View Stereo (MVS)
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## 功能
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https://sibr.gitlabpages.inria.fr/docs/0.9.6/projects.html
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- [Sample algorithms & toolboxes](https://sibr.gitlabpages.inria.fr/docs/0.9.6/sibr_projects_samples.html)
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- [Dataset Preprocessing Tools](https://sibr.gitlabpages.inria.fr/docs/0.9.6/sibr_projects_dataset_tools.html) ([https://gitlab.inria.fr/sibr/sibr_core](https://gitlab.inria.fr/sibr/sibr_core))
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- [Unstructured Lumigraph Rendering (ULR)](https://sibr.gitlabpages.inria.fr/docs/0.9.6/ulrPage.html) ([https://gitlab.inria.fr/sibr/sibr_core](https://gitlab.inria.fr/sibr/sibr_core))
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- [Our algorithms](https://sibr.gitlabpages.inria.fr/docs/0.9.6/sibr_projects_ours.html)
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- [Exploiting Repetitions for IBR of Facades](https://sibr.gitlabpages.inria.fr/docs/0.9.6/facade_repetitionsPage.html) ([https://gitlab.inria.fr/sibr/projects/facades-repetitions/facade_repetitions](https://gitlab.inria.fr/sibr/projects/facades-repetitions/facade_repetitions)) (Exploiting Repetitions for IBR of Facades (paper reference :[http://www-sop.inria.fr/reves/Basilic/2018/RBDD18/](http://www-sop.inria.fr/reves/Basilic/2018/RBDD18/)))
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- [Deep Blending for Free-Viewpoint Image-Based Rendering – Scalable Inside-Out Image-Based Rendering](https://sibr.gitlabpages.inria.fr/docs/0.9.6/inside_out_deep_blendingPage.html) ([https://gitlab.inria.fr/sibr/projects/inside_out_deep_blending](https://gitlab.inria.fr/sibr/projects/inside_out_deep_blending)) (Deep Blending for Free-Viewpoint Image-Based Rendering, paper references: [http://www-sop.inria.fr/reves/Basilic/2018/HPPFDB18/](http://www-sop.inria.fr/reves/Basilic/2018/HPPFDB18/) , [http://visual.cs.ucl.ac.uk/pubs/deepblending/](http://visual.cs.ucl.ac.uk/pubs/deepblending/) ; Scalable Inside-Out Image-Based Rendering, paper references: [http://www-sop.inria.fr/reves/Basilic/2016/HRDB16](http://www-sop.inria.fr/reves/Basilic/2016/HRDB16) , [http://visual.cs.ucl.ac.uk/pubs/insideout/](http://visual.cs.ucl.ac.uk/pubs/insideout/) )
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- [Multi-view relighting using a geometry-aware network](https://sibr.gitlabpages.inria.fr/docs/0.9.6/outdoorRelightingPage.html) ([https://gitlab.inria.fr/sibr/projects/outdoor_relighting](https://gitlab.inria.fr/sibr/projects/outdoor_relighting)) (Multi-view Relighting Using a Geometry-Aware Network; paper reference ([https://www-sop.inria.fr/reves/Basilic/2019/PGZED19/](https://www-sop.inria.fr/reves/Basilic/2019/PGZED19/)) )
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- [Image-Based Rendering of Cars using Semantic Labels and Approximate Reflection Flow](https://sibr.gitlabpages.inria.fr/docs/0.9.6/semantic_reflectionsPage.html) ([https://gitlab.inria.fr/sibr/projects/semantic-reflections/semantic_reflections](https://gitlab.inria.fr/sibr/projects/semantic-reflections/semantic_reflections)) (Image-Based Rendering of Cars using Semantic Labels and Approximate Reflection Flow (paper reference : [http://www-sop.inria.fr/reves/Basilic/2020/RPHD20/](http://www-sop.inria.fr/reves/Basilic/2020/RPHD20/)))
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- [Depth Synthesis and Local Warps for plausible image-based navigation - Bayesian approach for selective image-based rendering using superpixels](https://sibr.gitlabpages.inria.fr/docs/0.9.6/spixelwarpPage.html) ([https://gitlab.inria.fr/sprakash/spixelwarp](https://gitlab.inria.fr/sprakash/spixelwarp)) (Depth Synthesis and Local Warps for plausible image-based navigation, paper reference: [http://www-sop.inria.fr/reves/Basilic/2013/CDSD13/](http://www-sop.inria.fr/reves/Basilic/2013/CDSD13/) ; Bayesian approach for selective image-based rendering using superpixels, paper reference: [http://www-sop.inria.fr/reves/Basilic/2015/ODD15/](http://www-sop.inria.fr/reves/Basilic/2015/ODD15/) ))
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- [Glossy Probe Reprojection for Interactive Global Illumination](https://sibr.gitlabpages.inria.fr/docs/0.9.6/synthetic_ibrPage.html) ([https://gitlab.inria.fr/sibr/projects/glossy-probes/synthetic_ibr](https://gitlab.inria.fr/sibr/projects/glossy-probes/synthetic_ibr)) (Glossy Probe Reprojection for Interactive Global Illumination (paper reference : [http://www-sop.inria.fr/reves/Basilic/2020/RLPWSD20/](http://www-sop.inria.fr/reves/Basilic/2020/RLPWSD20/)))
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- [Other algorithms](https://sibr.gitlabpages.inria.fr/docs/0.9.6/sibr_projects_others.html)
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- [Soft3D](https://sibr.gitlabpages.inria.fr/docs/0.9.6/soft3dPage.html) ([https://gitlab.inria.fr/sibr/projects/soft3d](https://gitlab.inria.fr/sibr/projects/soft3d)) (Soft 3D Reconstruction for View Synthesis (paper reference : [https://ericpenner.github.io/soft3d/](https://ericpenner.github.io/soft3d/)))
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- [Integrated toolboxes](https://sibr.gitlabpages.inria.fr/docs/0.9.6/sibr_projects_toolbox.html)
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- [Core framework of FRIBR](https://sibr.gitlabpages.inria.fr/docs/0.9.6/fribrFrameworkPage.html) ([https://gitlab.inria.fr/sibr/fribr_framework](https://gitlab.inria.fr/sibr/fribr_framework)) (Core framework of FRIBR)
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- [SIBR/OptiX integration example](https://sibr.gitlabpages.inria.fr/docs/0.9.6/optixPage.html) ([https://gitlab.inria.fr/sibr/projects/optix](https://gitlab.inria.fr/sibr/projects/optix)) (SIBR/OptiX integration example)
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- [Simple SIBR Project](https://sibr.gitlabpages.inria.fr/docs/0.9.6/simplePage.html) ([https://gitlab.inria.fr/sibr/projects/simple](https://gitlab.inria.fr/sibr/projects/simple)) (A simple sample SIBR project for you to base your projects on)
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- [Tensorflow/OpenGL Interop for SIBR](https://sibr.gitlabpages.inria.fr/docs/0.9.6/tfgl_interopPage.html) ([https://gitlab.inria.fr/sibr/tfgl_interop](https://gitlab.inria.fr/sibr/tfgl_interop)) (Tensorflow GL interoperability dependencies and cuda code)
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- [示例算法和工具箱](https://sibr.gitlabpages.inria.fr/docs/0.9.6/sibr_projects_samples.html)
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- [数据集预处理工具](https://sibr.gitlabpages.inria.fr/docs/0.9.6/sibr_projects_dataset_tools.html)（[https://gitlab.inria.fr/sibr/sibr_core](https://gitlab.inria.fr/sibr/sibr_core)）
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- [非结构化 Lumigraph 渲染 (ULR)](https://sibr.gitlabpages.inria.fr/docs/0.9.6/ulrPage.html) ( [https://gitlab.inria.fr/sibr/sibr_core](https://gitlab.inria.fr/sibr/sibr_core) )
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- [我们的算法](https://sibr.gitlabpages.inria.fr/docs/0.9.6/sibr_projects_ours.html)
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- [Exploiting Repetitions for IBR of Facades](https://sibr.gitlabpages.inria.fr/docs/0.9.6/facade_repetitionsPage.html) ( [https://gitlab.inria.fr/sibr/projects/facades-repetitions/facade_repetitions](https://gitlab.inria.fr/sibr/projects/facades-repetitions/facade_repetitions) ) (Exploiting Repetitions for IBR of Facades (论文参考： http: [//www-sop.inria.fr/里夫/巴西利克/2018/RBDD18/](http://www-sop.inria.fr/reves/Basilic/2018/RBDD18/)））
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- [用于基于自由视点图像的渲染的深度混合 – 可扩展的由内而外基于图像的渲染](https://sibr.gitlabpages.inria.fr/docs/0.9.6/inside_out_deep_blendingPage.html)( [https://gitlab.inria.fr/sibr/projects/inside_out_deep_blending](https://gitlab.inria.fr/sibr/projects/inside_out_deep_blending) ) （用于基于自由视点图像的渲染的深度混合，论文参考：[http://www-sop.inria.fr/reves/Basilic/2018/HPPFDB18/，http](http://www-sop.inria.fr/reves/Basilic/2018/HPPFDB18/) : [//visual.cs.ucl.ac.uk/pubs/deepblending/](http://visual.cs.ucl.ac.uk/pubs/deepblending/)；可扩展的由内而外基于图像的渲染，论文参考：[http://www-sop.inria.fr/reves/Basilic/2016/HRDB16，http](http://www-sop.inria.fr/reves/Basilic/2016/HRDB16) : [//visual.cs.ucl.ac.uk/pubs/insideout/](http://visual.cs.ucl.ac.uk/pubs/insideout/)）
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- [使用几何感知网络的多视图重新照明](https://sibr.gitlabpages.inria.fr/docs/0.9.6/outdoorRelightingPage.html)( [https://gitlab.inria.fr/sibr/projects/outdoor_relighting](https://gitlab.inria.fr/sibr/projects/outdoor_relighting) )（使用几何感知网络的多视图重新照明；论文参考 ( [https://www-sop. inria.fr/reves/Basilic/2019/PGZED19/](https://www-sop.inria.fr/reves/Basilic/2019/PGZED19/) ) )
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- [使用语义标签和近似反射流的基于图像的汽车渲染](https://sibr.gitlabpages.inria.fr/docs/0.9.6/semantic_reflectionsPage.html)（[https://gitlab.inria.fr/sibr/projects/semantic-reflections/semantic_reflections](https://gitlab.inria.fr/sibr/projects/semantic-reflections/semantic_reflections)）（使用语义标签和近似反射流的基于图像的汽车渲染（论文参考：[http://www-sop.inria.fr/reves/Basilic/2020/RPHD20/](http://www-sop.inria.fr/reves/Basilic/2020/RPHD20/)））
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- [用于合理的基于图像的导航的深度合成和局部扭曲 - 使用超像素进行选择性基于图像的渲染的贝叶斯方法](https://sibr.gitlabpages.inria.fr/docs/0.9.6/spixelwarpPage.html)（[https://gitlab.inria.fr/sprakash/spixelwarp](https://gitlab.inria.fr/sprakash/spixelwarp)）（用于合理的基于图像的导航的深度合成和局部扭曲，论文参考：[http://www-sop.inria.fr/reves/Basilic/2013/CDSD13/](http://www-sop.inria.fr/reves/Basilic/2013/CDSD13/)；使用超像素进行选择性基于图像渲染的贝叶斯方法，论文参考： http: [//www-sop.inria.fr/里夫/巴西利克/2015/ODD15/](http://www-sop.inria.fr/reves/Basilic/2015/ODD15/)））
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- [用于交互式全局照明的光泽探针重投影](https://sibr.gitlabpages.inria.fr/docs/0.9.6/synthetic_ibrPage.html)（[https://gitlab.inria.fr/sibr/projects/glossy-probes/synthetic_ibr](https://gitlab.inria.fr/sibr/projects/glossy-probes/synthetic_ibr)）（用于交互式全局照明的光泽探针重投影（论文参考：[http://www-sop.inria。 fr/reves/Basilic/2020/RLPWSD20/](http://www-sop.inria.fr/reves/Basilic/2020/RLPWSD20/) ))
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- [其他算法](https://sibr.gitlabpages.inria.fr/docs/0.9.6/sibr_projects_others.html)
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- [Soft3D](https://sibr.gitlabpages.inria.fr/docs/0.9.6/soft3dPage.html)（[https://gitlab.inria.fr/sibr/projects/soft3d](https://gitlab.inria.fr/sibr/projects/soft3d)）（用于视图合成的软3D重建（论文参考： https: [//ericpenner.github.io/soft3d/](https://ericpenner.github.io/soft3d/)））
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- [集成工具箱](https://sibr.gitlabpages.inria.fr/docs/0.9.6/sibr_projects_toolbox.html)
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- [FRIBR核心框架](https://sibr.gitlabpages.inria.fr/docs/0.9.6/fribrFrameworkPage.html)（[https://gitlab.inria.fr/sibr/fribr_framework）（FRIBR](https://gitlab.inria.fr/sibr/fribr_framework)核心框架）
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- [SIBR/OptiX 集成示例](https://sibr.gitlabpages.inria.fr/docs/0.9.6/optixPage.html)( [https://gitlab.inria.fr/sibr/projects/optix](https://gitlab.inria.fr/sibr/projects/optix) )（SIBR/OptiX 集成示例）
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- [简单 SIBR 项目](https://sibr.gitlabpages.inria.fr/docs/0.9.6/simplePage.html)( [https://gitlab.inria.fr/sibr/projects/simple](https://gitlab.inria.fr/sibr/projects/simple) )（一个简单的示例 SIBR 项目，供您作为项目的基础）
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- [SIBR 的 Tensorflow/OpenGL 互操作](https://sibr.gitlabpages.inria.fr/docs/0.9.6/tfgl_interopPage.html)（[https://gitlab.inria.fr/sibr/tfgl_interop）（Tensorflow](https://gitlab.inria.fr/sibr/tfgl_interop) GL 互操作性依赖项和 cuda 代码）
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项目结构:
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- `renderer/`: contains your library code and configuration
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- `preprocess/`: contains your preprocesses listed by directory, and the configuration CMake file to list them
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- `apps/`: contains your apps listed by directory, and the configuration CMake file to list them
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- `documentation/`: contains additional doxygen documentation
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# SIBR数据集创建方式
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**SIBR**本身定义了一种数据格式
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可以使用**RealityCapture**或者**Colmap**创建原生的SIBR数据集，也可以根据文档使用SFM或者MVS系统创建兼容数据集合。
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- [如何从 Reality Capture 创建数据集](https://sibr.gitlabpages.inria.fr/docs/0.9.6/HowToCapreal.html)
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- [如何从 Colmap 创建数据集](https://sibr.gitlabpages.inria.fr/docs/0.9.6/HowToColmap.html)
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官方提供的案例数据集:https://repo-sam.inria.fr/fungraph/sibr-datasets/museum_front27_ulr.zip
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# 运行案例方式
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下载编译好的版本
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>SIBR_ulrv2_app_rwdi.exe --path C:/Downloads/museum_front27_ulr/museum_front27/sibr_cm sibr -museum-front |