<p>I did only quick google search and found this PhD thesis - &quot;Inverse rendering for computer graphics&quot; by [Marschner1998] - <a href="http://graphics.stanford.edu/%7Esrm/thesis/thesis.pdf" rel="nofollow noreferrer">http://graphics.stanford.edu/~srm/thesis/thesis.pdf</a></p>
<p>Also two published papers - Ramamoorthi et al &quot;A Signal-Processing Framework for Inverse Rendering&quot; <a href="http://cseweb.ucsd.edu/%7Eravir/papers/invrend/invrend.pdf" rel="nofollow noreferrer">http://cseweb.ucsd.edu/~ravir/papers/invrend/invrend.pdf</a></p>
<p>And Yu, Smith - &quot;InverseRenderNet: Learning Single image inverse -
<a href="https://openaccess.thecvf.com/content_CVPR_2019/papers/Yu_InverseRenderNet_Learning_Single_Image_Inverse_Rendering_CVPR_2019_paper.pdf" rel="nofollow noreferrer">https://openaccess.thecvf.com/content_CVPR_2019/papers/Yu_InverseRenderNet_Learning_Single_Image_Inverse_Rendering_CVPR_2019_paper.pdf</a></p>
<hr />
<p>Based on my experience, just follow prior works in this area and you'll get to the first or first worth mentioning paper in this area. With every paper in the area of raytracing, you'll get reference to [Whitted1980]. Every BRDF will get you back to
[CT1967] and every Spherical Harmonics work to [Green2003].</p>
<p>Based on what you wrote, you must be familiar with reading papers. Therefore, I would suggest to read &quot;Introduction&quot; and &quot;Prior work&quot; to find references to past works in this area of computer graphics.</p>

CC BY-SA 4.0
2020-09-11T12:26:18.243Z
I found already the first two references you pointed out. But they're not deep learning based, I'm already aware of Whitted1980 and CT1967 but they have nothing to do with inverse rendering. Based on the thesis Inverse rendering it self has nothing to do with deep learning (I personally thought it was something *enabled* by Deep Learning, but I was wrong). I'm doing my research at the moment. The rendering network you pointed out is interesting, but it's dated 2019 and I have a feeling Inverse Rendering with Deep Learning started before that. But I can start with that I guess.
user8469759
CC BY-SA 4.0
2020-09-11T15:58:46.350Z
I am aware that they're not related. It was just meant to be an example of "basic papers" in other areas of computer graphics. I'm not sure if you understood me correctly. What I meant was to use references at the end of papers to find related works. In Yu/Smith work from 2019, I found in reference section this paper - http://papers.neurips.cc/paper/5851-deep-convolutional-inverse-graphics-network.pdf - Kulkarni et al 2015 - Deep Convolutional Inverse Graphics Network.
DirectX_Programmer
CC BY-SA 4.0
2020-09-11T16:04:38.383Z
I understood what you meant, essentially start from whatever paper I find and navigate backwards through the references until I find the first paper.
user8469759
CC BY-SA 4.0
2020-09-11T07:41:25.353Z
2020-09-11T07:41:25.353Z
DirectX_Programmer
<p>I only discovered there was name for it last Siggraph despite it being around, here is good introduction <a href="https://diff-render.org/" rel="nofollow noreferrer">https://diff-render.org/</a> with lots of references to more specialized topics. Can somebody confirm this phd thesis the earliest work on it? <a href="https://www.graphics.cornell.edu/pubs/1998/Mar98.pdf" rel="nofollow noreferrer">https://www.graphics.cornell.edu/pubs/1998/Mar98.pdf</a></p>

CC BY-SA 4.0
2021-09-05T07:49:49.547Z
2021-09-05T07:49:49.547Z
user501743
<p>I'm not sure this is the right place to ask for this reference but it's worth the shot since it is graphics related.</p>
<p>I'm looking for the very first paper describing what &quot;Inverse Rendering&quot; - By that I mean a machine learning system that given some renderer and a deep learning model and an image as input will provide you one or more maps describing how to render the same image.</p>
<p>I cannot manage to find anywhere a/the white paper the would describe how such system would work.</p>
<p>Can anyone provide a reference? Maybe not the very first paper but a white paper that might describe the fundamentals (I'd rather prefer papers to web articles).</p>
<p>Thank you</p>

<rendering>
Reference for Inverse Rendering
user8469759
# Reference for Inverse Rendering

(Asked by: username_0 on 2020-09-10)

I'm not sure this is the right place to ask for this reference but it's worth the shot since it is graphics related.

I'm looking for the very first paper describing what "Inverse Rendering" - By that I mean a machine learning system that given some renderer and a deep learning model and an image as input will provide you one or more maps describing how to render the same image.

I cannot manage to find anywhere a/the white paper the would describe how such system would work.

Can anyone provide a reference? Maybe not the very first paper but a white paper that might describe the fundamentals (I'd rather prefer papers to web articles).

Thank you

**Tags:** rendering


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## 2 answers

### Answer by username_2 on 2021-09-05. Score: 2

I only discovered there was name for it last Siggraph despite it being around, here is good introduction <https://diff-render.org/> with lots of references to more specialized topics. Can somebody confirm this phd thesis the earliest work on it? <https://www.graphics.cornell.edu/pubs/1998/Mar98.pdf>


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### Answer by username_1 on 2020-09-11. Score: 1

I did only quick google search and found this PhD thesis - "Inverse rendering for computer graphics" by [Marschner1998] - [http://graphics.stanford.edu/~srm/thesis/thesis.pdf](http://graphics.stanford.edu/%7Esrm/thesis/thesis.pdf)

Also two published papers - Ramamoorthi et al "A Signal-Processing Framework for Inverse Rendering" [http://cseweb.ucsd.edu/~ravir/papers/invrend/invrend.pdf](http://cseweb.ucsd.edu/%7Eravir/papers/invrend/invrend.pdf)

And Yu, Smith - "InverseRenderNet: Learning Single image inverse -
<https://openaccess.thecvf.com/content_CVPR_2019/papers/Yu_InverseRenderNet_Learning_Single_Image_Inverse_Rendering_CVPR_2019_paper.pdf>

---

Based on my experience, just follow prior works in this area and you'll get to the first or first worth mentioning paper in this area. With every paper in the area of raytracing, you'll get reference to [Whitted1980]. Every BRDF will get you back to
[CT1967] and every Spherical Harmonics work to [Green2003].

Based on what you wrote, you must be familiar with reading papers. Therefore, I would suggest to read "Introduction" and "Prior work" to find references to past works in this area of computer graphics.

> **Comments:**
> **username_0**: I found already the first two references you pointed out. But they're not deep learning based, I'm already aware of Whitted1980 and CT1967 but they have nothing to do with inverse rendering. Based on the thesis Inverse rendering it self has nothing to do with deep learning (I personally thought it was something *enabled* by Deep Learning, but I was wrong). I'm doing my research at the moment. The rendering network you pointed out is interesting, but it's dated 2019 and I have a feeling Inverse Rendering with Deep Learning started before that. But I can start with that I guess.  
> **username_1**: I am aware that they're not related. It was just meant to be an example of "basic papers" in other areas of computer graphics. I'm not sure if you understood me correctly. What I meant was to use references at the end of papers to find related works. In Yu/Smith work from 2019, I found in reference section this paper - http://papers.neurips.cc/paper/5851-deep-convolutional-inverse-graphics-network.pdf - Kulkarni et al 2015 - Deep Convolutional Inverse Graphics Network.  
> **username_0**: I understood what you meant, essentially start from whatever paper I find and navigate backwards through the references until I find the first paper.  

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