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Computer vision is so dope. You can map your space in real-time with the phone in your pocket — creating a simplified 3D model with ‘semantically meaningful’ entities representing the room, walls, windows and furniture within that space. Basically, a 3D floor plan. This is Apple’s aptly named Room...

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Bilawal Sidhu

107,188 subscribers

136,380 просмотров • 2 лет назад •via X (Twitter)

ОбразованиеНаука и технологииНовости и политика
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The new Krea 3D feature is insanely good. You can turn an image into a 3D model to move & rotate in space - and it guides real-time scene generation. Watch me move this couch around a living room ⬇️
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The new Krea 3D feature is insanely good. You can turn an image into a 3D model to move & rotate in space - and it guides real-time scene generation. Watch me move this couch around a living room ⬇️

Justine Moore

32,728 просмотров • 1 год назад

✨ 3d models are now LIVE on Photo AI 😊 You can now turn any AI photo you make into a 3d model by pressing [ 📦 Make 3d model ] And then you can view it inside Photo AI or download it as a .GLB 3d model file It's still very early in AI generated 3d model world but it's nice to have this feature working already As always, the models will keep improving, so this feature will keep getting better (like it did with video, it sucked before, now it's getting passable) Next would be nice to switch to .USDZ so you can load it straight into your iPhone with ARKit and put it in your room Available now for everyone on the Premium and Ultra plan
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✨ 3d models are now LIVE on Photo AI 😊 You can now turn any AI photo you make into a 3d model by pressing [ 📦 Make 3d model ] And then you can view it inside Photo AI or download it as a .GLB 3d model file It's still very early in AI generated 3d model world but it's nice to have this feature working already As always, the models will keep improving, so this feature will keep getting better (like it did with video, it sucked before, now it's getting passable) Next would be nice to switch to .USDZ so you can load it straight into your iPhone with ARKit and put it in your room Available now for everyone on the Premium and Ultra plan

@levelsio

112,930 просмотров • 1 год назад

honestly no surprise why Silicon Valley is so obsessed with Matic robots right now > basically a Roomba on steroids > vacuums first, then mops > uses five cameras to build a live 3D map of your home > recognizes rugs, wires, furniture, pets, and people, then changes how it cleans > point at a mess and say “hey Matic, clean this” and it does > an NVIDIA Jetson inside the robot handles all the vision, mapping, and navigation > raw footage is discarded in real time and your 3D map never leaves the device btw that last privacy part is extremely underrated IMO my biggest fear with robotics is putting moving cameras and microphones inside our most private spaces without knowing where the data goes. > this week, camera components on Royal Navy drones were caught phoning home to China > Chinese Unitree robot dogs were found with a backdoor that let anyone with the key remotely control them and watch through their cameras > Roombas sent images from inside homes to overseas labelers, including a woman on the toilet and a child your home is your most sacred private space. if you're gonna buy a robot that can physically record, map, and move through it, make sure it's secure!
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honestly no surprise why Silicon Valley is so obsessed with Matic robots right now > basically a Roomba on steroids > vacuums first, then mops > uses five cameras to build a live 3D map of your home > recognizes rugs, wires, furniture, pets, and people, then changes how it cleans > point at a mess and say “hey Matic, clean this” and it does > an NVIDIA Jetson inside the robot handles all the vision, mapping, and navigation > raw footage is discarded in real time and your 3D map never leaves the device btw that last privacy part is extremely underrated IMO my biggest fear with robotics is putting moving cameras and microphones inside our most private spaces without knowing where the data goes. > this week, camera components on Royal Navy drones were caught phoning home to China > Chinese Unitree robot dogs were found with a backdoor that let anyone with the key remotely control them and watch through their cameras > Roombas sent images from inside homes to overseas labelers, including a woman on the toilet and a child your home is your most sacred private space. if you're gonna buy a robot that can physically record, map, and move through it, make sure it's secure!

Ole Lehmann

45,092 просмотров • 13 дней назад

nano banana 2's understanding of dimension and 3D space is so crazy now, its like a personal designer in your pocket step 1: go to -> edit image -> select nano banana 2 -> upload floor plan -> type prompt (reply here if you want my prompt)
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nano banana 2's understanding of dimension and 3D space is so crazy now, its like a personal designer in your pocket step 1: go to -> edit image -> select nano banana 2 -> upload floor plan -> type prompt (reply here if you want my prompt)

el.cine

60,009 просмотров • 5 месяцев назад

China just dropped an open source model that turns any phone into a 3D scanner you point it at a room and walk through it the whole space builds itself into a 3D point cloud in real time as the camera moves, no LiDAR and no depth sensor anywhere it held a full 13 minute walkthrough at 25,000 frames without the map drifting or collapsing > ~20 fps on a single GPU > works indoors and outdoors from plain footage > the scan normally needs a $50,000 rig and a technician > Apache 2.0 and runs fully offline on your machine repo in the reply
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China just dropped an open source model that turns any phone into a 3D scanner you point it at a room and walk through it the whole space builds itself into a 3D point cloud in real time as the camera moves, no LiDAR and no depth sensor anywhere it held a full 13 minute walkthrough at 25,000 frames without the map drifting or collapsing > ~20 fps on a single GPU > works indoors and outdoors from plain footage > the scan normally needs a $50,000 rig and a technician > Apache 2.0 and runs fully offline on your machine repo in the reply

savip

104,123 просмотров • 1 месяц назад

Maket AI launched an AI Editor that can generate and change a whole floor plan as you type, in real-time. > "Add an office." > "Swap the kitchen and dining room." > "Make the living room bigger." Everyone is an interior designer now 👀
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Maket AI launched an AI Editor that can generate and change a whole floor plan as you type, in real-time. > "Add an office." > "Swap the kitchen and dining room." > "Make the living room bigger." Everyone is an interior designer now 👀

🚨 AI News | TestingCatalog

115,086 просмотров • 4 месяцев назад

Under the hood visionOS creates a full floor plan of your space as you use it, and labels everything (floor, ceiling, chairs, etc). This is no joke. Most people dont realize the foundations in place here that will unlock a wide possibility of experiences.
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Under the hood visionOS creates a full floor plan of your space as you use it, and labels everything (floor, ceiling, chairs, etc). This is no joke. Most people dont realize the foundations in place here that will unlock a wide possibility of experiences.

Ludovic Landry

297,611 просмотров • 2 лет назад

The last thing you see in your first and last Space Travel MiniMax H3 prompt: amateur handheld pov footage of a tourist in their plush and comfortable room of a space cruise, carpeted floor and comfy bed, large window shows a view of Gargantua blackhole, you can see their reflection in the window, they turn off the light half way through so we can see outside better and say: "Wow look at that!", then they show back the room
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The last thing you see in your first and last Space Travel MiniMax H3 prompt: amateur handheld pov footage of a tourist in their plush and comfortable room of a space cruise, carpeted floor and comfy bed, large window shows a view of Gargantua blackhole, you can see their reflection in the window, they turn off the light half way through so we can see outside better and say: "Wow look at that!", then they show back the room

Ivan Fioravanti ᯅ

10,416 просмотров • 16 дней назад

Do you know what your OpenClaw agents are actually doing? If not, bookmark this. Here is a complete 3D neural command center for monitoring agents, nodes, logs, and live activity in real time you can build yourself with this prompt. FULL PROMPT: I’ll upload a GitHub soon with the working files for all the projects I’ve shared so far. Notis on.
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Do you know what your OpenClaw agents are actually doing? If not, bookmark this. Here is a complete 3D neural command center for monitoring agents, nodes, logs, and live activity in real time you can build yourself with this prompt. FULL PROMPT: I’ll upload a GitHub soon with the working files for all the projects I’ve shared so far. Notis on.

Jayden ⛩️

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Wonderland: Navigating 3D Scenes from a Single Image Contributions: • First, we introduce a representation for controllable 3D generation by leveraging the generative priors from camera-guided video diffusion models. Unlike image models, video diffusion models are trained on extensive video datasets. This enables them to capture comprehensive spatial relationships within scenes across multiple views and embed a form of "3D awareness" in their latent space, which allows us to maintain 3D consistency in novel view synthesis. • Second, to achieve controllable novel view generation, we empower video models with precise control over specified camera motions. We introduce a novel dual-branch conditioning mechanism that effectively incorporates desired diverse camera trajectories into the video diffusion model. This enables expansion of a single image into a multi-view consistent capture of a 3D scene with precise pose control. • Third, to achieve efficient 3D reconstruction, we directly transform video latents into 3DGS. We propose a novel latent-based large reconstruction model (LaLRM) that lifts video latents to 3D in a feed-forward manner. With this design, during inference, our model directly predicts 3DGS from a single input image, effectively aligning the generation and reconstruction tasks—and bridging image space and 3D space—through the video latent space. Compared with reconstructing scenes from images, the video latent space offers a 256× spatial-temporal reduction while retaining essential and consistent 3D structural details. Such a high degree of compression is crucial, as it allows the LaLRM to handle a wider range of 3D scenes within the reconstruction framework, with the same memory constraints.
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Wonderland: Navigating 3D Scenes from a Single Image Contributions: • First, we introduce a representation for controllable 3D generation by leveraging the generative priors from camera-guided video diffusion models. Unlike image models, video diffusion models are trained on extensive video datasets. This enables them to capture comprehensive spatial relationships within scenes across multiple views and embed a form of "3D awareness" in their latent space, which allows us to maintain 3D consistency in novel view synthesis. • Second, to achieve controllable novel view generation, we empower video models with precise control over specified camera motions. We introduce a novel dual-branch conditioning mechanism that effectively incorporates desired diverse camera trajectories into the video diffusion model. This enables expansion of a single image into a multi-view consistent capture of a 3D scene with precise pose control. • Third, to achieve efficient 3D reconstruction, we directly transform video latents into 3DGS. We propose a novel latent-based large reconstruction model (LaLRM) that lifts video latents to 3D in a feed-forward manner. With this design, during inference, our model directly predicts 3DGS from a single input image, effectively aligning the generation and reconstruction tasks—and bridging image space and 3D space—through the video latent space. Compared with reconstructing scenes from images, the video latent space offers a 256× spatial-temporal reduction while retaining essential and consistent 3D structural details. Such a high degree of compression is crucial, as it allows the LaLRM to handle a wider range of 3D scenes within the reconstruction framework, with the same memory constraints.

MrNeRF

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We are officially entering the Aptos era! For any team building in the blockchain space performance is the ultimate foundation for success. Right now the network is leading the entire industry with a staggering block time of 0.04 seconds completely redefining what efficiency means. And also it's important to mention that, real world adoption requires infrastructure that can deliver instant results for millions of users simultaneously. When you combine this level of speed with reliability the possibilities become endless. Big respect to the team for making this vision a reality! Source: Chainspect

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This is our collaboration with a cool Ukrainian film. This film is also about space. It is called: You are space. It has been in theaters for 5 weeks and the audience continues to come. Find a chance to see it - it is cool.#jittergame #тикосмос

JITTER – Early Access Out Now! 🇺🇦

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Reminder: every Hugging Face Space is an API your agents can call :) I asked mine to build a website about the flowers of France 🌸 and it used VAST AI's TripoSplat Space to turn photos it found into real 3D Gaussian splats, live on the page! All on my HF Pro daily ZeroGPU credits (40 min/day renewed daily for only $9/month)

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As announced in partnership with NVIDIA at CES, we’re excited to introduce Stable Point Aware 3D (SPAR3D), setting a new standard in 3D generation. Ideal for running on NVIDIA RTX AI PCs, SPAR3D enables real-time editing and complete structure generation of 3D objects from a single image in under a second. You can download the weights on Hugging Face and code on GitHub, or access the model through the Stability AI API. Learn more here: (1/3)
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As announced in partnership with NVIDIA at CES, we’re excited to introduce Stable Point Aware 3D (SPAR3D), setting a new standard in 3D generation. Ideal for running on NVIDIA RTX AI PCs, SPAR3D enables real-time editing and complete structure generation of 3D objects from a single image in under a second. You can download the weights on Hugging Face and code on GitHub, or access the model through the Stability AI API. Learn more here: (1/3)

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