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Adobe.. has released a tool that combines Generative Gaussian Splats with a Diffusion layer and it's not all over the internet? WHAT IS GOING ON :D I had to test this out ofc! Substance 3D viewer, the new 3d viewer just released by Adobe, not only supports viewing of...

279,936 次观看 • 1 年前 •via X (Twitter)

9 条评论

Martin Nebelong 的头像
Martin Nebelong1 年前

The animation towards the end was made with Luma Dream btw.

Martin Nebelong 的头像
Martin Nebelong1 年前

Just going to leave this here and say.. I told you so! :D

SoqllooS 的头像
SoqllooS1 年前

Because adobe is a cancer of the creative industry. Anyone who has been in the industry for even a few years knows that. Now they trying to recover from gigantic criticism of the entire industry a few months ago. As soon as they improve their PR a bit, they'll be ripping again.

Martin Nebelong 的头像
Martin Nebelong1 年前

Let's give them a bit of credit for having revolutionized the industry as well.. I remember the early days of Photoshop, the introduction of more refined digital painting tools and there's lots of things to cherish still. The whole debacle around the TOS could have been handled better, but also seemed to have been blown a bit out of proportions. The criticism around subscription costs.. I think the price I pay for the Adobe suite each month is OK.

Bob 的头像
Bob1 年前

Nothing would ever cause me to give them another penny

不俱戴天 // Jose 的头像
不俱戴天 // Jose1 年前

> A new exciting AI tool! 👀👀 > Made by Adobe. Why would we support one of the worst and anti consumer company ever in history.

William Hurst 的头像
William Hurst1 年前

Because fuck Adobe. Thats why.

Martin Nebelong 的头像
Martin Nebelong1 年前

Yes, for now it's boring in terms of actual creative control. Most Gen ai is like that still.. We need much better tools to wield this tech. I'm sure that will come.

algorusty — (Christ/acc➟✞) 的头像
algorusty — (Christ/acc➟✞)1 年前

So this is what Adobe was stealing all your data for

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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.

AK

249,494 次观看 • 2 年前