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Slate dominated by the Queen Glory... how does such a big and scary Mudwing end up in these situations is a mystery to me 3D models of the Glory and the Rainwings (male and female) available for download with 3D Model Access tier on my Pete

Raptie

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91,687 次观看 • 8 个月前 •via X (Twitter)

Anya Rossi• Live Now

Private livecam show

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The latest free version of UE5 AVATAR is now available! This update enhances real-time rendering quality and adds hundreds of new digital clothing and accessories. Create personalized 3D models, customize outfits, select scenes, and connect AI motion capture for real-time rendered 3D animations. Anyone can create 3D character models—no professional modeling skills required. Future versions will support 3D model import/export and image-based 3D model generation. Get the download link in the comments!

CYANPUPPETS

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3D-LLM: Injecting the 3D World into Large Language Models paper page: Large language models (LLMs) and Vision-Language Models (VLMs) have been proven to excel at multiple tasks, such as commonsense reasoning. Powerful as these models can be, they are not grounded in the 3D physical world, which involves richer concepts such as spatial relationships, affordances, physics, layout, and so on. In this work, we propose to inject the 3D world into large language models and introduce a whole new family of 3D-LLMs. Specifically, 3D-LLMs can take 3D point clouds and their features as input and perform a diverse set of 3D-related tasks, including captioning, dense captioning, 3D question answering, task decomposition, 3D grounding, 3D-assisted dialog, navigation, and so on. Using three types of prompting mechanisms that we design, we are able to collect over 300k 3D-language data covering these tasks. To efficiently train 3D-LLMs, we first utilize a 3D feature extractor that obtains 3D features from rendered multi- view images. Then, we use 2D VLMs as our backbones to train our 3D-LLMs. By introducing a 3D localization mechanism, 3D-LLMs can better capture 3D spatial information. Experiments on ScanQA show that our model outperforms state-of-the-art baselines by a large margin (e.g., the BLEU-1 score surpasses state-of-the-art score by 9%). Furthermore, experiments on our held-in datasets for 3D captioning, task composition, and 3D-assisted dialogue show that our model outperforms 2D VLMs. Qualitative examples also show that our model could perform more tasks beyond the scope of existing LLMs and VLMs.

3D-LLM: Injecting the 3D World into Large Language Models paper page: Large language models (LLMs) and Vision-Language Models (VLMs) have been proven to excel at multiple tasks, such as commonsense reasoning. Powerful as these models can be, they are not grounded in the 3D physical world, which involves richer concepts such as spatial relationships, affordances, physics, layout, and so on. In this work, we propose to inject the 3D world into large language models and introduce a whole new family of 3D-LLMs. Specifically, 3D-LLMs can take 3D point clouds and their features as input and perform a diverse set of 3D-related tasks, including captioning, dense captioning, 3D question answering, task decomposition, 3D grounding, 3D-assisted dialog, navigation, and so on. Using three types of prompting mechanisms that we design, we are able to collect over 300k 3D-language data covering these tasks. To efficiently train 3D-LLMs, we first utilize a 3D feature extractor that obtains 3D features from rendered multi- view images. Then, we use 2D VLMs as our backbones to train our 3D-LLMs. By introducing a 3D localization mechanism, 3D-LLMs can better capture 3D spatial information. Experiments on ScanQA show that our model outperforms state-of-the-art baselines by a large margin (e.g., the BLEU-1 score surpasses state-of-the-art score by 9%). Furthermore, experiments on our held-in datasets for 3D captioning, task composition, and 3D-assisted dialogue show that our model outperforms 2D VLMs. Qualitative examples also show that our model could perform more tasks beyond the scope of existing LLMs and VLMs.

AK

249,798 次观看 • 3 年前

Fun visually-grounded 3d visualization with Muse Spark - by asking the model to generate a 3d visualization of how much each component cost on a xbox 360 motherboard (and put the bar on the component).

Fun visually-grounded 3d visualization with Muse Spark - by asking the model to generate a 3d visualization of how much each component cost on a xbox 360 motherboard (and put the bar on the component).

Fei Xia

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in the clurb, we all hate ads >:[ Thank yall so much for making my 3D debut stream so magical!! 🥹 I had such a great time with yall today 🧡 big thanks to MushmallowVT for the 3D models and for helping me figure out VNyan

in the clurb, we all hate ads >:[ Thank yall so much for making my 3D debut stream so magical!! 🥹 I had such a great time with yall today 🧡 big thanks to MushmallowVT for the 3D models and for helping me figure out VNyan

Clover 🍀🐮

20,934 次观看 • 9 个月前

Here's a look behind the scenes of how I used a 3d model, generated from an image, as a "driver" for ai animation. In the near future we'll see more 3d tools that support these types of workflows, with much more emphasis on enhancing user input instead of just letting the ai do everything. I used the 3d model to generate keyframes that I then animated in Luma Dream. By using a 3d model with a diffusion "layer" done with Krea, I got quite high quality frames with a relatively high consistency as well since the AI didn't have to "hallucinate" that much. I upscaled and detailed the frames using Magnific. Using semi-detailed 3d models as drivers for gen ai is very powerful, and it allows us to use models that are sculpted in a more free-flowing type of workflow that doesn't rely so much on high surface detailing or very time-consuming finish, but instead relies more on gestural 3d sculpting. #art #ai

Here's a look behind the scenes of how I used a 3d model, generated from an image, as a "driver" for ai animation. In the near future we'll see more 3d tools that support these types of workflows, with much more emphasis on enhancing user input instead of just letting the ai do everything. I used the 3d model to generate keyframes that I then animated in Luma Dream. By using a 3d model with a diffusion "layer" done with Krea, I got quite high quality frames with a relatively high consistency as well since the AI didn't have to "hallucinate" that much. I upscaled and detailed the frames using Magnific. Using semi-detailed 3d models as drivers for gen ai is very powerful, and it allows us to use models that are sculpted in a more free-flowing type of workflow that doesn't rely so much on high surface detailing or very time-consuming finish, but instead relies more on gestural 3d sculpting. #art #ai

Martin Nebelong

48,280 次观看 • 2 年前

INTRODUCING FLOPPI IN 3D!!! Thanks to: Andy-O is WRAPPING UP HNAUTS?! for working with me on the original design Valz for designing the banger 3D model Flapcats🔞 for not only rigging the model, but also making this animation and also making a tall version of Floppi #floppiart

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INTRODUCING FLOPPI IN 3D!!! Thanks to: Andy-O is WRAPPING UP HNAUTS?! for working with me on the original design Valz for designing the banger 3D model Flapcats🔞 for not only rigging the model, but also making this animation and also making a tall version of Floppi #floppiart

MENTLE

823,063 次观看 • 3 年前

Is this a 3D model? mfw you very clearly aren't the only one who knows how to create 3d models. and you use blender lolololololol

Is this a 3D model? mfw you very clearly aren't the only one who knows how to create 3d models. and you use blender lolololololol

Satoshi Nakamoto, Andrew Rulnick

23,700 次观看 • 9 个月前

Introducing Meta Locate 3D: a model for accurate object localization in 3D environments. Learn how Meta Locate 3D can help robots accurately understand their surroundings and interact more naturally with humans. You can download the model and dataset, read our research paper, and even try a demo!

Introducing Meta Locate 3D: a model for accurate object localization in 3D environments. Learn how Meta Locate 3D can help robots accurately understand their surroundings and interact more naturally with humans. You can download the model and dataset, read our research paper, and even try a demo!

AI at Meta

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after my ringfit stream today with my 3d model and setting up rebocap for it the tracking is just so good and its so easy to set up, i gotta get a full 3d model now im genuinely obsessed this is crazy you can see everything so accurately?? even in a chibi model with stub arms??

after my ringfit stream today with my 3d model and setting up rebocap for it the tracking is just so good and its so easy to set up, i gotta get a full 3d model now im genuinely obsessed this is crazy you can see everything so accurately?? even in a chibi model with stub arms??

Bri 🍪 VTUBER // LIVE2D RIGGER!

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My Fav part! Share a scripture with me on “GLORY” I’ll go first; “The voice of the Lord makes the deer give birth, And strips the forests bare; And in His temple everyone says, “Glory!”” Psalms 29:9 OGO available on all digital platforms. Youtube:

My Fav part! Share a scripture with me on “GLORY” I’ll go first; “The voice of the Lord makes the deer give birth, And strips the forests bare; And in His temple everyone says, “Glory!”” Psalms 29:9 OGO available on all digital platforms. Youtube:

Dunsin Oyekan of #Geni

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To generate 3D models in Codex with text-to-cad: Start a new project, write your prompt for a 3D model, and include a link to clone the text-to-cad repo. Codex handles the rest. The repo is open source and all scripts / ui run locally. Link below.

To generate 3D models in Codex with text-to-cad: Start a new project, write your prompt for a 3D model, and include a link to clone the text-to-cad repo. Codex handles the rest. The repo is open source and all scripts / ui run locally. Link below.

Jake Fitzgerald

22,113 次观看 • 4 个月前

Text-to-3D Generation with Bidirectional Diffusion using both 2D and 3D priors paper page: Most 3D generation research focuses on up-projecting 2D foundation models into the 3D space, either by minimizing 2D Score Distillation Sampling (SDS) loss or fine-tuning on multi-view datasets. Without explicit 3D priors, these methods often lead to geometric anomalies and multi-view inconsistency. Recently, researchers have attempted to improve the genuineness of 3D objects by directly training on 3D datasets, albeit at the cost of low-quality texture generation due to the limited texture diversity in 3D datasets. To harness the advantages of both approaches, we propose Bidirectional Diffusion(BiDiff), a unified framework that incorporates both a 3D and a 2D diffusion process, to preserve both 3D fidelity and 2D texture richness, respectively. Moreover, as a simple combination may yield inconsistent generation results, we further bridge them with novel bidirectional guidance. In addition, our method can be used as an initialization of optimization-based models to further improve the quality of 3D model and efficiency of optimization, reducing the generation process from 3.4 hours to 20 minutes. Experimental results have shown that our model achieves high-quality, diverse, and scalable 3D generation.

Text-to-3D Generation with Bidirectional Diffusion using both 2D and 3D priors paper page: Most 3D generation research focuses on up-projecting 2D foundation models into the 3D space, either by minimizing 2D Score Distillation Sampling (SDS) loss or fine-tuning on multi-view datasets. Without explicit 3D priors, these methods often lead to geometric anomalies and multi-view inconsistency. Recently, researchers have attempted to improve the genuineness of 3D objects by directly training on 3D datasets, albeit at the cost of low-quality texture generation due to the limited texture diversity in 3D datasets. To harness the advantages of both approaches, we propose Bidirectional Diffusion(BiDiff), a unified framework that incorporates both a 3D and a 2D diffusion process, to preserve both 3D fidelity and 2D texture richness, respectively. Moreover, as a simple combination may yield inconsistent generation results, we further bridge them with novel bidirectional guidance. In addition, our method can be used as an initialization of optimization-based models to further improve the quality of 3D model and efficiency of optimization, reducing the generation process from 3.4 hours to 20 minutes. Experimental results have shown that our model achieves high-quality, diverse, and scalable 3D generation.

AK

38,853 次观看 • 2 年前

The female carries the mystery. In Moby Dick, it's the sea that's female and the sea carries the mystery. In Lawrence of Arabia, the desert is the female and the movie is shot to make the desert look gorgeous. In detective movies, you'll have a male detective and a female femme fatale who carries the mystery. Pressfield says: "That's a principle I have: the female carries the mystery. And I'll ask myself of any idea I have: what's the female in this story? Is there a mystery? What is the mystery? The mystery is almost always something that cannot be solved. It's like: What is life? What is death? And it gets back to God. It gets back to creation. It gets back to life."

The female carries the mystery. In Moby Dick, it's the sea that's female and the sea carries the mystery. In Lawrence of Arabia, the desert is the female and the movie is shot to make the desert look gorgeous. In detective movies, you'll have a male detective and a female femme fatale who carries the mystery. Pressfield says: "That's a principle I have: the female carries the mystery. And I'll ask myself of any idea I have: what's the female in this story? Is there a mystery? What is the mystery? The mystery is almost always something that cannot be solved. It's like: What is life? What is death? And it gets back to God. It gets back to creation. It gets back to life."

David Perell

168,415 次观看 • 8 个月前

Claude Fable 5 built a 3D product website with Claude Code Generate an image of a product with the Magnific MCP, and convert it into a 3D model. Download that model and give it to Fable 5 to develop an interactive page with. Here's the final result + prompts:

Claude Fable 5 built a 3D product website with Claude Code Generate an image of a product with the Magnific MCP, and convert it into a 3D model. Download that model and give it to Fable 5 to develop an interactive page with. Here's the final result + prompts:

Jerrod Lew

33,687 次观看 • 3 个月前

dude Astra with a 3D model generator is fucking insane i gave it access to the 3D AI Studio MCP and told it to make Rocket League it generated the assets itself and built this:

dude Astra with a 3D model generator is fucking insane i gave it access to the 3D AI Studio MCP and told it to make Rocket League it generated the assets itself and built this:

Jan

236,140 次观看 • 7 天前

TXTRCast by せう🍩 is a Blender add-on that lets you paint textures in software like CSP and Photoshop and see the updates live on your 3D model. Available for free:

TXTRCast by せう🍩 is a Blender add-on that lets you paint textures in software like CSP and Photoshop and see the updates live on your 3D model. Available for free:

80 LEVEL

58,340 次观看 • 2 个月前