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"Absolutely zero AI was used." SavageCG reworked Blender's Metallic BSDF using 5,403 nodes and data from research papers, bringing over 30 physically accurate metal materials with more to come.

78,339 次观看 • 2 个月前 •via X (Twitter)

16 条评论

80 LEVEL 的头像
80 LEVEL2 个月前

It's available for free:

Goblin 的头像
Goblin2 个月前

honestly if you're able to translate research papers into nodes it would have probably been easier to do this with the actual BSDF code rather than 5000+ nodes

Dylan Amos 的头像
Dylan Amos2 个月前

Funny how the first words on the post needs to be "Absolutely zero AI was used". I feel that even mentioning that takes the focus away from the developers achievement as there's a lot more interesting snippets that could have been used instead based on the article.

RusselStudios 的头像
RusselStudios2 个月前

5403 nodes deliver accuracy but what about viewport lag and file bloat? Sometimes simpler shaders win for actual production deadlines.

Samurai Frog 的头像
Samurai Frog2 个月前

Wow! Everything from shiny to shiny with scratches! Weve really hit the heights now boy!

MOCHA 的头像
MOCHA2 个月前

Looks tedious. Just give me the final output so I can get on with my life.

Thomas Andersen 的头像
Thomas Andersen2 个月前

Then optimized down to five nodes for use in real‑time game‑engine rendering.

Mawntee 的头像
Mawntee2 个月前

holy shit

b2kdaman | Extraction Quake | sceneBG Addon 的头像
b2kdaman | Extraction Quake | sceneBG Addon2 个月前

AUTISM vs AI

Landon Looper 的头像
Landon Looper2 个月前

@agni_flare All that time manually making this mess?.. Its not doing the AI allergic tech art crowd any favors to tout a 5000+ node rat's nest as the performative poster child. Hand-crafting a solution should (and can often) be more elegant & maintainable. This is sadly quite the opposite.

Shane Killian 的头像
Shane Killian2 个月前

Am I the only one dumb enough not to be able to find the download link?

Brian the 3D Guy 的头像
Brian the 3D Guy2 个月前

What's the performance like? Seems like that would be heavy.

Alien Ant World 🛸 的头像
Alien Ant World 🛸2 个月前

Cool

Alex_tu 的头像
Alex_tu2 个月前

没用任何AI,会是一个相当不错的宣传语

Ellie 🎀 的头像
Ellie 🎀2 个月前

5,403 nodes of spite

Visual Chris 的头像
Visual Chris2 个月前

Submit this to blender foundation pls

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PhD Students – How to automatically extract data from papers for your literature review? Extracting relevant data from papers is challenging. However, this process can be automated. Meet AnswerThis – a tool that extracts data in seconds. Here is how it works. 1. Go to and log in. 2. After logging in, click on 𝐸𝑥𝑡𝑟𝑎𝑐𝑡 𝑑𝑎𝑡𝑎. 3. Then click on 𝑈𝑝𝑙𝑜𝑎𝑑 𝑃𝐷𝐹 and upload your papers. 4. These are the papers from which you want to extract data. 5. After uploading papers, select data you want to extract. 6. The predefined options are - Key findings - Research gaps - Methodology - Limitations - Future work - Contributions - Practical implications 7. You can also extract custom data e.g., dataset used. 8. For example, I want to extract methodology used in these papers. 9. I selected 𝑀𝑒𝑡ℎ𝑜𝑑𝑜𝑙𝑜𝑔𝑦 and clicked on 𝐴𝑑𝑑 𝐶𝑜𝑙𝑢𝑚𝑛. 10. AnswerThis extract data about methodology used in the papers. 11. You can change data view from normal to Table View. 12. For this, scroll back to top and click on 𝑇𝑎𝑏𝑙𝑒 𝑉𝑖𝑒𝑤. 13. Now for instance, you want to extract more data from these papers. 14. Go back to the top and click on 𝐸𝑥𝑡𝑟𝑎𝑐𝑡 𝑑𝑎𝑡𝑎. 15. Select the data type you want to extract. 16. For example, I want to extract data about future work. 17. So I click on 𝐹𝑢𝑡𝑢𝑟𝑒 𝑊𝑜𝑟𝑘 and then clicked on 𝐴𝑑𝑑 𝑐𝑜𝑙𝑢𝑚𝑛. 18. AnswerThis extracted data about future work from the papers. 19. After extracting the desired data, you can export it. 20. Select the data you want to extract. 21. Then click on 𝐸𝑥𝑝𝑜𝑟𝑡 𝑑𝑎𝑡𝑎. 22. Your data will be exported in CSV format. You can then analyze this data for your literature review. Try AnswerThis today: Anything you'd like to add?

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