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SceneScript treats 3D reconstruction as a language problem rather than a geometry one. The model watches a video of a room and just learns to write a script for it. It autoregressively spits out text commands like make_wall(...) or make_bbox(...) that define the scene. Stanford's new "Scene Language" paper... show more

Bilawal Sidhu

106,372 subscribers

107,011 görüntüleme • 11 ay önce •via X (Twitter)

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Bilawal Sidhu profil fotoğrafı

Bilawal Sidhu11 ay önce

Semantic 3d scene understanding is absolutely crucial for robotics and spatial computing devices like AR and VR headsets.

Bilawal Sidhu profil fotoğrafı

Bilawal Sidhu11 ay önce

Paper/project here. Need to fill out a form to get access to model weights:

Bilawal Sidhu profil fotoğrafı

Bilawal Sidhu11 ay önce

Enjoyed this post? You might also enjoy my monthly newsletter:

Nev (unsupervised) profil fotoğrafı

Nev (unsupervised)11 ay önce

I was working in construction when the iPhone 12 Pro came out and I used the LiDAR scanner for EVERYTHING, my boss thought it was sort of gimmicky at first but I could tell he liked it after a couple days of me finding apps that created detailed depth maps and showed inconsistencies in the dug paths where slate was to be laid down, this is almost exactly what I imagined the next evolution would be

LazyFit profil fotoğrafı

LazyFit1 yıl önce

No jumping, No Running. Workouts at home at any time.🕒🏠 BEST 15 min Beginner Home Workout for Weight Loss 🧘‍♀️🔥

Andreas Klinger 🦾 profil fotoğrafı

Andreas Klinger 🦾11 ay önce

this is really cool and obvious thing that they dont mention is how this could be used to also create simpler vocabulary for a scene you could define an object in the room give it a boundary box and a name like objectX and then say "task: carry objectX to table3" or event: table3 moved to cordination xy

Dan Brickley profil fotoğrafı

Dan Brickley11 ay önce

Can it work from a Gaussian Splat scene?

Max Vox (fka Duke Zero) profil fotoğrafı

Max Vox (fka Duke Zero)11 ay önce

fung shui module wen?

David Branca profil fotoğrafı

David Branca11 ay önce

Very cool!

Andres Franco profil fotoğrafı

Andres Franco11 ay önce

Really cool stuff. Can’t wait to see where this ends up going.

Gordon Olson profil fotoğrafı

Gordon Olson11 ay önce

Special understanding goes so far. This is what will truly open up the full potential of AI. The possibilities will transgress new frontiers. This is an exciting part of that. Very cool!

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Meta announces SceneScript Reconstructing Scenes With An Autoregressive Structured Language Model We introduce SceneScript, a method that directly produces full scene models as a sequence of structured language commands using an autoregressive, token-based approach. Our

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AK

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Turns out that vision-language models can control robots too. The secret is to just finetune them to print out the actions (literally, as text). Really excited about our new result, the successor to RT-1. RT-2 is a pre-trained VLM: Short 🧵👇

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AI + robotics research is starting to pick up steam. We can now instruct Spot using natural language using Language-guided Skill Coordination (LSC). A user provides a natural language instruction: "Bring me the chocolates box, cereal box, and pill bottle, and put them on the bedroom table" and the robot navigates to the location of the target objects and places them on the room table. Current versions of Spot rely on a fixed-set vocabulary that cannot generalize to diverse instructions. In this demo, the researchers presented a method that uses large language models to receive a free-form natural language instruction for object rearrangement, which it then executes. It combines: -A voice-to-text model that processes the instructions into text -An LLM that converts natural language instruction to call a library of skills -A perception module that provides ground truth locations and visual object detection And what your left with is a glimpse into what our future will hold: robots executing tasks from human voice prompts.

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Spatial reasoning is a major challenge for the foundation models today, even in simple tasks like arranging objects in 3D space. #CVPR2025 Introducing LayoutVLM, a differentiable optimization framework that uses VLM to spatially reason about diverse scene layouts from unlabeled assets and open-ended language instructions 1/n

Spatial reasoning is a major challenge for the foundation models today, even in simple tasks like arranging objects in 3D space. #CVPR2025 Introducing LayoutVLM, a differentiable optimization framework that uses VLM to spatially reason about diverse scene layouts from unlabeled assets and open-ended language instructions 1/n

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Saw a clip a of #Pacers forward Obi Toppin doing ASL. Finally asked him about it. “I was supposed to take a language in HS. … I ain’t want to take Spanish or (another verbal language) — it was hard doing that. So, it was like, ‘Sign language might be the easiest one.’” 😂

Saw a clip a of #Pacers forward Obi Toppin doing ASL. Finally asked him about it. “I was supposed to take a language in HS. … I ain’t want to take Spanish or (another verbal language) — it was hard doing that. So, it was like, ‘Sign language might be the easiest one.’” 😂

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MotionGPT: Human Motion as a Foreign Language paper page: Though the advancement of pre-trained large language models unfolds, the exploration of building a unified model for language and other multi-modal data, such as motion, remains challenging and untouched so far. Fortunately, human motion displays a semantic coupling akin to human language, often perceived as a form of body language. By fusing language data with large-scale motion models, motion-language pre-training that can enhance the performance of motion-related tasks becomes feasible. Driven by this insight, we propose MotionGPT, a unified, versatile, and user-friendly motion-language model to handle multiple motion-relevant tasks. Specifically, we employ the discrete vector quantization for human motion and transfer 3D motion into motion tokens, similar to the generation process of word tokens. Building upon this "motion vocabulary", we perform language modeling on both motion and text in a unified manner, treating human motion as a specific language. Moreover, inspired by prompt learning, we pre-train MotionGPT with a mixture of motion-language data and fine-tune it on prompt-based question-and-answer tasks. Extensive experiments demonstrate that MotionGPT achieves state-of-the-art performances on multiple motion tasks including text-driven motion generation, motion captioning, motion prediction, and motion in-between.

MotionGPT: Human Motion as a Foreign Language paper page: Though the advancement of pre-trained large language models unfolds, the exploration of building a unified model for language and other multi-modal data, such as motion, remains challenging and untouched so far. Fortunately, human motion displays a semantic coupling akin to human language, often perceived as a form of body language. By fusing language data with large-scale motion models, motion-language pre-training that can enhance the performance of motion-related tasks becomes feasible. Driven by this insight, we propose MotionGPT, a unified, versatile, and user-friendly motion-language model to handle multiple motion-relevant tasks. Specifically, we employ the discrete vector quantization for human motion and transfer 3D motion into motion tokens, similar to the generation process of word tokens. Building upon this "motion vocabulary", we perform language modeling on both motion and text in a unified manner, treating human motion as a specific language. Moreover, inspired by prompt learning, we pre-train MotionGPT with a mixture of motion-language data and fine-tune it on prompt-based question-and-answer tasks. Extensive experiments demonstrate that MotionGPT achieves state-of-the-art performances on multiple motion tasks including text-driven motion generation, motion captioning, motion prediction, and motion in-between.

AK

125,319 görüntüleme • 3 yıl önce

How the British tried erase the Irish Language. Years ago, I debated one of those finance types, who saw language only as useful, to the extent it facilitated international trade and science/technology. It is extremely dangerous to reduce a people's language to that. Language encapsulates a society's worldview, its way of thinking, and other intangible attributes.

How the British tried erase the Irish Language. Years ago, I debated one of those finance types, who saw language only as useful, to the extent it facilitated international trade and science/technology. It is extremely dangerous to reduce a people's language to that. Language encapsulates a society's worldview, its way of thinking, and other intangible attributes.

Onye Nkuzi

95,753 görüntüleme • 7 ay önce

Today we're opening up a new experimental multiplayer worldbuilding tool called "Patchwork". It combines language models, image models, and a canvas-based interface to build out the foundations of stories. Check out the 🧵below for links and further documentation. Have fun!

Today we're opening up a new experimental multiplayer worldbuilding tool called "Patchwork". It combines language models, image models, and a canvas-based interface to build out the foundations of stories. Check out the 🧵below for links and further documentation. Have fun!

Midjourney

254,252 görüntüleme • 1 yıl önce

Chatbots aren’t the revolution. They’re the distraction. Fei-Fei Li: “Language is a half-million-year-old luxury. Perception is a half-billion-year-old necessity.” Evolution didn’t optimize for conversation. It optimized for survival in three-dimensional space. Seeing threats, navigating obstacles, predicting what happens when you move. We’ve spent years celebrating AI that can write and summarize. But text processing is narrow. Spatial intelligence is fundamental. An agent that only reads prompts can’t function in a warehouse or a hospital. It needs to parse depth, understand physics, and act on what it sees in real time. We built AI that understands language. Now we’re building AI that understands space. Language models got the attention. Spatial intelligence gets the work done. The world runs on physics, not paragraphs. AI is learning to operate in it.

Chatbots aren’t the revolution. They’re the distraction. Fei-Fei Li: “Language is a half-million-year-old luxury. Perception is a half-billion-year-old necessity.” Evolution didn’t optimize for conversation. It optimized for survival in three-dimensional space. Seeing threats, navigating obstacles, predicting what happens when you move. We’ve spent years celebrating AI that can write and summarize. But text processing is narrow. Spatial intelligence is fundamental. An agent that only reads prompts can’t function in a warehouse or a hospital. It needs to parse depth, understand physics, and act on what it sees in real time. We built AI that understands language. Now we’re building AI that understands space. Language models got the attention. Spatial intelligence gets the work done. The world runs on physics, not paragraphs. AI is learning to operate in it.

Dustin

51,715 görüntüleme • 4 ay önce