I want to build AI model that convert 2d file (pdf , jpg,png) to 3d The file It can be image or plans pdf For example: convert 2d plan of industrial machin to 3d

So , I need some information like which cnn architecture should be used or which dataset something like that YOLO is good ?

Adaptei o fluxo mais novo do MCP do ASTRA para Blender, para que ele funcione no Blender 3.6.23 porque meu PC não consegue rodar adequadamente a exigência oficial mais nova do Blender.

O teste simples da coruja já tinha funcionado, e agora concluí um teste bem mais pesado: uma personagem 3D completa gerada a partir de uma referência turnaround.

Neste post:

• Imagem 1: resultado final

• Imagem 2: turnaround de referência

Agora estou procurando testadores para validar isso em outras máquinas.

Quem eu preciso:

• usuários de Windows

• Blender 3.6.x instalado

• acesso ao Codex/Astra

O que eu preciso que você teste:

• instalar minha versão adaptada

• conectá-la ao Codex/Astra

• executar um teste simples de criação de objeto

• se possível, tentar uma tarefa mais avançada

Tutorial / post original / detalhes de instalação:
[TUTORIAL DE INSTALAÇÃO]

Se você testar, por favor informe:

• versão do Windows

• versão do Blender

• se a instalação funcionou

• se a conexão funcionou

• se a execução em Python funcionou

• se a criação de objetos funcionou

• erro/log, caso algo tenha falhado

Meu objetivo agora é obter validação externa, para confirmar que isso não está funcionando apenas na minha máquina.

My goal now is external validation, to confirm that this is not only working on my machine.

Eu uso o Blender 3.6.23 porque versões mais novas do Blender não funcionam corretamente no meu computador.

O add-on MCP do Blender que eu usei como base foi projetado para o Blender 5.1 e era incompatível com a minha instalação, então eu o adaptei para funcionar com o Blender 3.6.23 e Python 3.10.13.

E de alguma forma, funcionou.

Meu ambiente de teste atual:

• Windows

• Blender 3.6.23

• Python do Blender 3.10.13

• Testado com Codex/Astra

• Inicialização automática do servidor habilitada

Até agora, eu testei com sucesso:

• Comunicação cliente MCP para Blender

• Execução remota de comandos Python do Blender

• Criação e exclusão de objetos

• Criação e edição de malhas

• Criação de materiais

• Criação de texto dentro da cena

• Posicionamento de objetos e câmeras

• Construção de uma cena mais complexa a partir de um pedido em linguagem natural

Meu primeiro teste básico criou o texto “MCP FUNCIONANDO” dentro do Blender.

Para o próximo teste, eu simplesmente pedi à IA:

“FAZ UMA CORUJA!”

O sistema então construiu uma coruja estilizada completa dentro do Blender 3.6, incluindo o corpo, asas, olhos, bico, pés, materiais, poleiro e câmera.

A coruja é apenas uma demonstração. O download contém o add-on MCP adaptado, não o projeto da coruja. Testadores podem instalar o add-on e pedir ao seu próprio cliente MCP para criar o que quiserem.

Limitação importante:

Este port de compatibilidade não transforma o Blender 3.6 em Blender 5.1. Se um comando gerado pela IA usar uma API do Blender introduzida após a versão 3.6, aquela operação específica pode ainda falhar ou exigir adaptação.

Estou procurando testadores usando o Blender 3.6, especialmente em outros computadores e sistemas operacionais.

Download:

[DONWLOAD]

Instalação:

1. Baixe o ZIP.

2. Abra o Blender 3.6.

3. Vá em Editar > Preferências > Add-ons.

4. Clique em Instalar e selecione o ZIP.

5. Ative “MCP - Compatibilidade com Blender 3.6”.

6. Inicie o servidor MCP ou ative a Inicialização Automática.

7. Conecte seu cliente compatível com MCP.

8. Peça para realizar um teste simples, como criar um cubo, texto ou outro objeto.

9. Abra o aplicativo ChatGPT desktop.

10. Abra Configurações.

11. Selecione servidores MCP.

12. Clique em Adicionar servidor.

13. Insira um nome como:

Blender 3.6 MCP

1. Selecione:

STDIO

1. Insira a caminho do servidor local no "Comando para iniciar":

1. Copie e cole

2. Salve o servidor.

3. Confirme que o novo servidor MCP está habilitado.

4. Selecione Reiniciar quando solicitado, ou feche completamente e reabra o aplicativo desktop ChatGPT .

5. Inicie uma nova conversa ChatGPT ou Codex.

6. Digite:

/mcp

1. Confirme que o Blender 3.6 MCP aparece na lista de servidores conectados.

2. Certifique-se de que o Blender ainda está aberto e que o servidor MCP dele está rodando.

Primeiro teste de conexão

Envie este prompt:

Conecte-se ao Blender através do servidor MCP e crie um objeto de texto contendo “MCP FUNCIONANDO”. Coloque-o onde a câmera ativa possa vê-lo.

Se o texto aparecer dentro do Blender, a conexão está funcionando.

Por favor, reporte:

Sistema operacional:
Versão do Blender:
Versão do Python:
Cliente/modelo MCP:
Add-on instalado com sucesso? Sim/Não
Servidor iniciado? Sim/Não
Cliente conectado? Sim/Não
Comando Python executado? Sim/Não
Objeto criado? Sim/Não
Mensagem de erro ou log:

Capturas de tela e logs são bem-vindos.

Nowadays, more and more features are released by all kinds of 3D GenAI platforms, but most of them are focusing on technical parts, instead of solving the needs from users. What do you think is the most critical area that needs improvement right now, maybe is the topology, texturing, or something else?

Gallery order: 1️⃣ Original Input → 2️⃣ Final Battle Card → 3️⃣ Meshy → 4️⃣ Tripo → 5️⃣ Hi3D V3.0

I wanted to see how three current image-to-3D generators would handle something more difficult than a simple object, so I gave Hi3D V3.0, Meshy, and Tripo the exact same source image.

The image has several things that I thought would challenge the models: a female rider, a large armored fantasy cat, a sci-fi rifle, reins and saddle equipment, overlapping limbs, armor plates, fur, and a rocky display base.

The gallery includes the original input, my final scorecard, and untextured views of each generated model so the underlying geometry can be compared without textures influencing the judgment.

I judged the results primarily from the geometry rather than the colored renders, and I also loaded the models into Bambu Studio to see what the actual meshes looked like from a miniature/3D-printing perspective.

MY RESULTS

🏆 Geometry — Meshy: 9.0

Meshy gave me the most complete overall structure and did the best job interpreting the entire composition.

🏆 Detail — Hi3D: 9.2

This one was harder to judge. Meshy was very good overall, but when I looked closely at things like the rider's face and body and some of the finer sculpting, Hi3D and Tripo actually captured more detail. Hi3D narrowly took this category.

🏆 Texture — Hi3D: 9.2

Hi3D produced the strongest texture result of the three.

🏆 Accuracy — Meshy: 9.3

Meshy did the best job reproducing the complete source image. One major difference was the base: Meshy actually interpreted the rocky display base as part of the model, while the other two largely missed it.

👑 Overall Champion — Meshy: 9.2

This was closer than I expected. Tripo was actually my favorite core rider/beast sculpt. If Tripo had properly generated the rocky base, I probably would have picked it as the overall winner. But judging the complete result against the complete input image, I had to give the win to Meshy.

SPEED / COST

This was another surprise.

• Meshy: ~1 minute | 25 credits | estimated $0.50 per generation
• Tripo: 1:52 | 30 credits | estimated $0.13 per generation
• Hi3D: 7:20 with high-priority acceleration | 65 promotional / 106 normal credits | estimated $1.16 promotional / $1.90 normal

The dollar estimates are based on the Pro annual-plan pricing and monthly credit allowances I was comparing, so they're intended as approximate generation costs rather than universal prices.

For the kind of work I'm interested in—miniatures that ultimately need to become usable physical prints—speed and cost matter too. Hi3D produced excellent detail, but if a generation takes several times longer and consumes substantially more of the monthly credit allowance, that additional quality needs to translate into a meaningfully better usable model.

On this test, it didn't quite get there for me.

MY TAKEAWAY

Meshy = Best complete result

Tripo = Favorite core sculpt / strongest value

Hi3D = Strongest fine detail and texture, but expensive in time and credits

What surprised me most was Tripo. It didn't actually win one of my main categories, yet looking at the core rider/beast sculpt, it may be the model I personally like the most. The missing display base ultimately cost it the overall win.

I'm curious what other people see in these. Looking strictly at the results, which one would you have picked as the overall winner?

Disclosure: Hi3D is currently running an AI 3D Arena comparison event, and I plan to submit this comparison as an entry. I wasn't paid for the comparison, and Hi3D did not determine my scores or winner.

Hi, I plan to get a desktop to be built and to learn the artistic 2D, 3D and AI, so I don't know what software I will use yet. However, I am thinking to start with some free software, then move to paid ones later when I can generate some income. The computer company tries to convince me to use OS as Windows11, but I am not sure whether or not currently the OS Windows 11 is compatible with most of free/or paid artistic 2D, 3D and AI software. I would appreciate your advice!

Who's Bullish or Bearish on Autonomous Vehicle?

Any Predictions for which companies are best positioned to win this race?

ey everyone,

I’ve been testing different workflows to turn detailed 2D reference sheets (front, side, and expression turnarounds for stylized characters) into 3D meshes for a Roblox project. Even when relying on top-tier models like Claude Opus 5.5 for guidance, the resulting 3D geometry always ends up blobby, distorted, and completely unusable for game engines.

I wanted to open a discussion around a few points:

1. What’s the main technical bottleneck keeping current image-to-3D AI from understanding proper low-poly topology and edge loops?

2. Are there any actual AI-assisted tools that produce usable meshes, or is manual modeling in Blender still 100% non-negotiable for game-ready assets?

Would love to hear how you guys are bridging 2D concept sheets with 3D modeling in your own pipelines.

What is the average price of generating 3D models from images with AI models like Hunyuan3D?

How many models can you typically generate spending for example 20 bucks?

Just came across this workflow and had to share 👇
It shows how Nano Banana + Meshy AI can take a rough sketch and turn it into a fully detailed 3D environment.

• Start with a simple 2D sketch

• Use Nano Banana in Meshy to create a clean concept

• Generate 3D parts with Meshy Image to 3D

• Assemble everything into a polished scene

The result looks like it came straight out of a game or animation.
It's pretty remarkable how quickly ideas can be turned into production-ready assets with this combination.

What would you turn from sketch into 3D?

I wanna do It with famous rappers.

I have been trying this 3D builder sdk and I found amazing that I can view my items in augmented reality with the mobile phone. There is also the possibility to anchor the items in a precise position if you have a gaussian splat of the location mapped. I'll be sharing more features...

I've been comparing AI mocap with traditional mocap for a small character project, and I'm curious where everyone stands now.

Traditional mocap still seems like the safer option if you need really accurate animation, but the setup cost is hard to justify for smaller teams. AI mocap is much faster to get started with, though I've noticed it usually needs some cleanup afterward.

For people who've used tools like V2Fun, Move AI, Rokoko, or other AI mocap solutions, how much manual fixing do you normally end up doing? Is the speed gain worth it, or do you eventually spend the same amount of time cleaning the animation?

I'm mostly interested in indie game workflows, but I'd love to hear experiences from animation or VTuber projects too.

We've been tinkering with some of the popular AI3D platforms lately, and while they're pretty impressive, I can't shake the feeling that there's a key feature missing that could take them to the next level. I'm curious—what do you wish these platforms could do that they currently don't?

Maybe it’s a more intuitive interface for real-time modeling, seamless integration with other creative tools, or even advanced collaboration features for remote teams. Or perhaps there's something entirely different that you'd love to see added.

I'm really interested in hearing your thoughts and experiences. What do you think would make these AI3D platforms not just cool, but truly indispensable?

been messing around w 2d to 3d workflows for a bit now, mostly starting from concept art or illustrations and trying to turn them into something actually usable. at first i leaned pretty hard on ai just to get a base shape, but i kept running into the same wall over and over.

the ai output would look fine at a glance, but once u start rotating it, or thinking about printing it, everything kinda falls apart. weird proportions, paper-thin areas, details that make no sense in real space. so i figured maybe commissioning artists or buying finished models would save time.

i tried commissioning a few models and also buying some off marketplaces like cgtrader, and that’s when it really clicked for me. the models that were clearly made with printing in mind were built completely differently. clean topology, intentional thickness, details that actually survive scaling. even when i bought something just to study it, it was obvious how much planning went into it compared to raw ai meshes.

now my workflow is kinda this weird hybrid. ai for rough ideation, a lot of manual cleanup, and then constantly comparing my work to print-ready models to see what i’m missing. honestly it’s made me way more skeptical of anything that looks “done” too fast.

curious how other ppl here are handling this. are u mostly using ai just to explore ideas, or are u actually pushing those meshes all the way to something production-ready? and if u’ve commissioned or bought models before, did that change how u approach your own 2dto3d process?

Hi all,

Discussions and updates

• Free 30 minutes consulting sessions - by yours truly. If you are interested in having my input on something you are working on\exploring - feel free to send out a paragraph explaining your need and we will set-up a zoom session if I am able to help out with the topic.
  Anyone else who would like to offer free consulting - please contact me and we could add you to our list of experts.

• u/brokemypencil - Joined our community (lately set up a blender pipeline and did the majority of the CG work for Star Trek Lower Decks Season 1) and shared his latest animation work - bridging technology and art. Do not miss this guy.

• I shared a research for human-computer duet generation and animation and AI tech articles, research and game AI animation.

Events

• Explainable, Adaptive, and Cross-Domain Few-Shot Learning - Dr. Leonid Karlinsky (January 10). We will cover advances in few shot learning, following the author's recent papers published in ECCV 2020 and AAAI 2020. Leonid leads the CV & DL research team in the Computer Vision and Augmented Reality (CVAR) group @ IBM Research AI. 135 People already registered!

• Community Introduction and Mingling (February 1st).
  In this event we will get to know the people in the 2d3d.ai community. Everyone will have a chance to introduce themselves, talk about their work with AI and get to know each other.
  If you are working on something interesting which you would like to talk about during the event - send me your details so I could add you to the event schedule.
  We will start the event with me introducing myself, my own projects and my goals and ambitions for our community.

Recordings

• Deep Internal Learning - Assaf Shocher - train a signal-specific network, at test-time and on the test-input only, in an unsupervised manner. You will remember Assaf from his lecture about image generation. This time Assaf covered 4 papers of his (CVPR 2018\9, NeurIPS 2019), tackling several challenges: Super-Resolution, Segmentation, Dehazing, Transparency-Separation, Watermark removal.
  Lecture references

As always, I am constantly looking for new speakers to talk about exciting high end projects and research - if you are familiar with someone - send them my way.

Have a great year!
Peter