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Depth Anything V2 is a total beast for real-time 3D. Built a website that hits 30fps+ depth reconstructions from a single camera feed, extruding 12k voxels via WebGPU. Pure ML running local Vision Transformers with Three.js and zero backend lag. Lmk in the comments if you want a copy!...

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Gábor Pribék

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142,337 görüntüleme • 4 ay önce •via X (Twitter)

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Vibe-coded a "Ponku" sticker experience to mirror how Apple is blending iPhone hardware with Korea Emojis. 🌈📱 3D iPhone by Ranguel on Sketchfab. Built with AI in Omma by Spline. Lmk in the comments if you would like to grab a copy of the experience!
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Vibe-coded a "Ponku" sticker experience to mirror how Apple is blending iPhone hardware with Korea Emojis. 🌈📱 3D iPhone by Ranguel on Sketchfab. Built with AI in Omma by Spline. Lmk in the comments if you would like to grab a copy of the experience!

Gábor Pribék

17,196 görüntüleme • 4 ay önce

HTML enters 3D! Or vice versa? With the new HTML in Canvas by WICG, we can finally put native DOM elements directly into WebGL/WebGPU scenes. It is experimental for now, but the possibilities for 3D interfaces and special effects are huge. This demo was built using Three.js and Omma AI (tool by Spline ) It’s a fun new way to explore what the web can do! Are you interested in seeing the demo?
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HTML enters 3D! Or vice versa? With the new HTML in Canvas by WICG, we can finally put native DOM elements directly into WebGL/WebGPU scenes. It is experimental for now, but the possibilities for 3D interfaces and special effects are huge. This demo was built using Three.js and Omma AI (tool by Spline ) It’s a fun new way to explore what the web can do! Are you interested in seeing the demo?

Gábor Pribék

176,349 görüntüleme • 4 ay önce

🤯 I didn’t expect Depth to track rooftop parkour this cleanly! Used a fast climbing clip as the motion reference, then swapped in a student with twin tails and a backpack on a coastal school rooftop. The running path, wall contact, jumps, landings, and full-body continuity all hold together surprisingly well. 🌟 Workflow: 1. Pick a reference clip under 15 seconds 2. Convert it to Depth with Depth Anything V2 3. Generate a new character + scene 4. Feed everything into Seedance with the prompt below 🌟 Depth video conversion: You can build a local Depth converter with Codex — prompt in the comments. Depth opens up a lot more possibilities for parkour, climbing, martial arts, dance, and other complex full-body motion. Workflow + Prompt below 👇
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🤯 I didn’t expect Depth to track rooftop parkour this cleanly! Used a fast climbing clip as the motion reference, then swapped in a student with twin tails and a backpack on a coastal school rooftop. The running path, wall contact, jumps, landings, and full-body continuity all hold together surprisingly well. 🌟 Workflow: 1. Pick a reference clip under 15 seconds 2. Convert it to Depth with Depth Anything V2 3. Generate a new character + scene 4. Feed everything into Seedance with the prompt below 🌟 Depth video conversion: You can build a local Depth converter with Codex — prompt in the comments. Depth opens up a lot more possibilities for parkour, climbing, martial arts, dance, and other complex full-body motion. Workflow + Prompt below 👇

Larus Canus

24,613 görüntüleme • 1 ay önce

🤯 Depth videos perfectly solve false flags on reference videos — and can perfectly recreate both martial arts and dance! Turned a Guan Dao martial arts clip into a Depth motion reference, swapped the fighter for a market auntie, and moved the scene to a T-junction inside a local market 🤣 🌟 Workflow: 1. Pick a reference clip under 15 seconds 2. Convert it to Depth with Depth Anything V2 3. Generate a new character + scene 4. Feed everything into Seedance with the prompt below 🌟 Depth video conversion: You can build a local Depth converter with Codex — prompt in the comments. This goes way beyond trending dances. Martial arts, polearms, and other complex movements can all be transferred cleanly with Depth! Workflow + Prompt below 👇
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🤯 Depth videos perfectly solve false flags on reference videos — and can perfectly recreate both martial arts and dance! Turned a Guan Dao martial arts clip into a Depth motion reference, swapped the fighter for a market auntie, and moved the scene to a T-junction inside a local market 🤣 🌟 Workflow: 1. Pick a reference clip under 15 seconds 2. Convert it to Depth with Depth Anything V2 3. Generate a new character + scene 4. Feed everything into Seedance with the prompt below 🌟 Depth video conversion: You can build a local Depth converter with Codex — prompt in the comments. This goes way beyond trending dances. Martial arts, polearms, and other complex movements can all be transferred cleanly with Depth! Workflow + Prompt below 👇

Larus Canus

50,904 görüntüleme • 1 ay önce

Kinda crazy we can now generate realistic-looking 3d models with AI, generated this one in Omma AI and built a #threejs scene around it as if it was a furniture website showcase. Live link: Here is an example prompt that I used:
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Kinda crazy we can now generate realistic-looking 3d models with AI, generated this one in Omma AI and built a #threejs scene around it as if it was a furniture website showcase. Live link: Here is an example prompt that I used:

Marco Fugaro

48,896 görüntüleme • 3 ay önce

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)

Stability AI

181,554 görüntüleme • 1 yıl önce

Nah no, this is not a pre-made or baked Blender model. It is created entirely from scratch using extruded geometry and procedural textures for the mustard hatching pattern on the model... all done with Google Gemini 3 pro AI. In fact, every Three.js 3D model you see on this website has been vibe coded with AI 😎 Live: Code:
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Nah no, this is not a pre-made or baked Blender model. It is created entirely from scratch using extruded geometry and procedural textures for the mustard hatching pattern on the model... all done with Google Gemini 3 pro AI. In fact, every Three.js 3D model you see on this website has been vibe coded with AI 😎 Live: Code:

The Bugged Dev

54,391 görüntüleme • 7 ay önce

going to regret this... $77K in 7 days. 1,630 orders. 3.38% conversion. every page built by AI in 60 seconds. 5 countries running from AI translations that took 4 minutes total. a backend depositing $25K/month from traffic I already paid for. I check my phone twice a day. the AI pages do the rest I put the full AI dropshipping system into a 36-page guide - how to find products from tiktok comments for $0, how AI builds pages that convert at 3.4%, the demographics that print, the $50 test protocol, international expansion in one afternoon, and the backend that turns $50K into $77K without new ad spend Comment "AI" and I'll send it over (must be following)
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going to regret this... $77K in 7 days. 1,630 orders. 3.38% conversion. every page built by AI in 60 seconds. 5 countries running from AI translations that took 4 minutes total. a backend depositing $25K/month from traffic I already paid for. I check my phone twice a day. the AI pages do the rest I put the full AI dropshipping system into a 36-page guide - how to find products from tiktok comments for $0, how AI builds pages that convert at 3.4%, the demographics that print, the $50 test protocol, international expansion in one afternoon, and the backend that turns $50K into $77K without new ad spend Comment "AI" and I'll send it over (must be following)

Alex Minecan

19,747 görüntüleme • 16 gün önce

In the new version of Simulon, we've built a simulated depth of field effect that seamlessly blends CG and real-world elements, mimicking the behavior of a real camera lens. We just love creating miniature shots with shallow focus! Assets by our friends at BigMediumSmall
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In the new version of Simulon, we've built a simulated depth of field effect that seamlessly blends CG and real-world elements, mimicking the behavior of a real camera lens. We just love creating miniature shots with shallow focus! Assets by our friends at BigMediumSmall

Divesh Naidoo

59,080 görüntüleme • 1 yıl önce

Along with @levelsio, we’re looking for the best games you make with AI. More in his tweet below. Cursor 3 has a built-in browser, image generation, and cloud agents that can playtest, while Composer 2 is fast with Three.js. Great for building games! Even developers at Rockstar are using AI now. Games can be built faster, made more beautiful and complex, and created by more people. It's surprisingly easy if you have no experience. The games shown below were already made with Cursor by Startracker 🔺, Danny Limanseta, David Bui, and Chong-U. Show us what you can build! Can't wait to see your submissions.
0:17

Along with @levelsio, we’re looking for the best games you make with AI. More in his tweet below. Cursor 3 has a built-in browser, image generation, and cloud agents that can playtest, while Composer 2 is fast with Three.js. Great for building games! Even developers at Rockstar are using AI now. Games can be built faster, made more beautiful and complex, and created by more people. It's surprisingly easy if you have no experience. The games shown below were already made with Cursor by Startracker 🔺, Danny Limanseta, David Bui, and Chong-U. Show us what you can build! Can't wait to see your submissions.

edwin

78,789 görüntüleme • 5 ay önce

ReViV reconstructs viewer-centric human motion (body, hand, and gaze) and view-centric scene geometry (camera and depth) from a single egocentric RGB video in a unified feed-forward model. It formulates the task as learning the full joint probability distribution over multimodal signals, including RGB video, camera trajectory, gaze direction, full-body motion, hand motion, and depth. Powered by a Masked Generative Egocentric Transformer, ReViV operates within a single feed-forward architecture to simultaneously reconstruct the temporally consistent 4D reconstruction across the viewer and the view with fast inference speed. Paper Title: ReViV: Reconstructing the Viewer and the View in 4D from Monocular Project: Link:
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ReViV reconstructs viewer-centric human motion (body, hand, and gaze) and view-centric scene geometry (camera and depth) from a single egocentric RGB video in a unified feed-forward model. It formulates the task as learning the full joint probability distribution over multimodal signals, including RGB video, camera trajectory, gaze direction, full-body motion, hand motion, and depth. Powered by a Masked Generative Egocentric Transformer, ReViV operates within a single feed-forward architecture to simultaneously reconstruct the temporally consistent 4D reconstruction across the viewer and the view with fast inference speed. Paper Title: ReViV: Reconstructing the Viewer and the View in 4D from Monocular Project: Link:

AI Bites | YouTube Channel

18,590 görüntüleme • 1 ay önce

I'll always root for a team that open-sources its best work, and Robbyant just did it properly. Robbyant, Ant Group's embodied-AI company, released LingBot-Vision, a vision foundation model for robots, and the part I love is the data. They trained it on 161M images, filtered down from 2B raw ones and mostly pulled straight from the open web, with no human labels, no edge detectors, no depth sensors anywhere in the loop. It learns the exact edges of objects from raw pixels. That's roughly a tenth of the data DINOv3 saw, and under a third of the training. And it shows in the results. On depth, working out how far away things are, the 1B model edges out a 7B on NYU-Depth. It also powers LingBot-Depth 2.0, which reads the surfaces cameras usually choke on, glass and mirrors, and halves indoor depth error. LingBot-Vision is fully open. Weights from the 1.1B flagship down to a tiny 21M version, code, and the paper. This is the timeline I want more of. Robbyant
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I'll always root for a team that open-sources its best work, and Robbyant just did it properly. Robbyant, Ant Group's embodied-AI company, released LingBot-Vision, a vision foundation model for robots, and the part I love is the data. They trained it on 161M images, filtered down from 2B raw ones and mostly pulled straight from the open web, with no human labels, no edge detectors, no depth sensors anywhere in the loop. It learns the exact edges of objects from raw pixels. That's roughly a tenth of the data DINOv3 saw, and under a third of the training. And it shows in the results. On depth, working out how far away things are, the 1B model edges out a 7B on NYU-Depth. It also powers LingBot-Depth 2.0, which reads the surfaces cameras usually choke on, glass and mirrors, and halves indoor depth error. LingBot-Vision is fully open. Weights from the 1.1B flagship down to a tiny 21M version, code, and the paper. This is the timeline I want more of. Robbyant

Chubby♨️

48,249 görüntüleme • 1 ay önce

Speaking of Dreams.. still kinda crazy to me how perfect of a match a tool like that is for generative AI workflows. Intuitive game engine/creative sandbox that allows you to build almost anything, running underneath a Gen AI render. Sculpting, painting, interacting with your two hands in 3d space, here using two move controllers which by now is tech from 2010. I haven't seen ANY way to interact with 3d that allows for the same fast and intuitive sculpting without forcing you to wear a VR headset. I made this scene a few years ago in 2 and a half hour or so as part of a 1 scene pr. episode of The Last of Us, and ran it through a combo of Runway and Sora to get to this result.
0:19

Speaking of Dreams.. still kinda crazy to me how perfect of a match a tool like that is for generative AI workflows. Intuitive game engine/creative sandbox that allows you to build almost anything, running underneath a Gen AI render. Sculpting, painting, interacting with your two hands in 3d space, here using two move controllers which by now is tech from 2010. I haven't seen ANY way to interact with 3d that allows for the same fast and intuitive sculpting without forcing you to wear a VR headset. I made this scene a few years ago in 2 and a half hour or so as part of a 1 scene pr. episode of The Last of Us, and ran it through a combo of Runway and Sora to get to this result.

Martin Nebelong

19,510 görüntüleme • 11 ay önce

AI-Enhanced LiDAR. Left vs right. A real LiDAR device costs thousands of dollars. What's in your iPhone Pro is a "baby LiDAR". Limited depth resolution, noisy output, not really built for high-precision 3D. You can't change the hardware. So we built an ML layer on top. Denoising, geometry completion, detail recovery. Processed server-side. Same sensor. Very different result.
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AI-Enhanced LiDAR. Left vs right. A real LiDAR device costs thousands of dollars. What's in your iPhone Pro is a "baby LiDAR". Limited depth resolution, noisy output, not really built for high-precision 3D. You can't change the hardware. So we built an ML layer on top. Denoising, geometry completion, detail recovery. Processed server-side. Same sensor. Very different result.

KIRI Engine - 3D Scanner App

51,787 görüntüleme • 3 ay önce

Google Earth now lets you create AI images using real-world locations. With the new Nano Banana AI feature, you can pick any place in Google Earth, click “Create Image,” and describe what you want to see. The AI can turn that location into a historical scene, a futuristic city or a fantasy world The feature uses Google Earth’s satellite and 3D map data as the base, so the AI-generated images are built from real locations.
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Google Earth now lets you create AI images using real-world locations. With the new Nano Banana AI feature, you can pick any place in Google Earth, click “Create Image,” and describe what you want to see. The AI can turn that location into a historical scene, a futuristic city or a fantasy world The feature uses Google Earth’s satellite and 3D map data as the base, so the AI-generated images are built from real locations.

Pirat_Nation 🔴

24,731 görüntüleme • 1 ay önce

3.5 Soon: Up to 8+ Layers, 16 LLMs in Parallel🪄 A fully parallel, multi-layered system with 8+ orchestration layers handling everything from prompt parsing and tool execution to code generation and live editing—all powered by 16+ LLMs running in sync for real-time, adaptive creation. ➡️v1: Single agent, single output ↕️v2: Multiple agents, single output 🔃v3: Single agent, multiple outputs 🔀v3.5: Multiple agents, multiple outputs — scalable, context-aware, and built for real-time builds🔨
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3.5 Soon: Up to 8+ Layers, 16 LLMs in Parallel🪄 A fully parallel, multi-layered system with 8+ orchestration layers handling everything from prompt parsing and tool execution to code generation and live editing—all powered by 16+ LLMs running in sync for real-time, adaptive creation. ➡️v1: Single agent, single output ↕️v2: Multiple agents, single output 🔃v3: Single agent, multiple outputs 🔀v3.5: Multiple agents, multiple outputs — scalable, context-aware, and built for real-time builds🔨

ALCHEMIST AI 🔮

13,482 görüntüleme • 1 yıl önce

🔥 AI video creation is finally evolving beyond basic motion prompts. Try out Depth Map Control right here: Historically, the hardest part of the process has been maintaining scene consistency: • camera movement • object placement • spatial relationships Thanks to PixVerse Depth Map Control, you can now grab depth data from a reference video and merge it with a fresh image to explore highly directed video generation. The final outcome? Much smoother camera tracking. Highly cohesive visual scenes. It is a powerful workflow that hands creators actual authority over how their AI visuals shift and flow over time. 🎬
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🔥 AI video creation is finally evolving beyond basic motion prompts. Try out Depth Map Control right here: Historically, the hardest part of the process has been maintaining scene consistency: • camera movement • object placement • spatial relationships Thanks to PixVerse Depth Map Control, you can now grab depth data from a reference video and merge it with a fresh image to explore highly directed video generation. The final outcome? Much smoother camera tracking. Highly cohesive visual scenes. It is a powerful workflow that hands creators actual authority over how their AI visuals shift and flow over time. 🎬

Elara Quinn

12,202 görüntüleme • 1 ay önce

🔥 Phoenix is officially live on Solaris AI Flow. You can now trade Phoenix perps inside a Solaris AI workflow. No code. Drop a node onto the canvas, pick an operation, and wire it to anything: AI signals, price feeds, schedules, alerts. The full order-book DEX from Ellipsis Labs, now programmable. Built so you can trade with confidence: ✦ Paper mode is on by default. Every order is checked and simulated against the live order book, real depth and real slippage, but nothing is signed or broadcast. ✦ Paper behaves exactly like Live. If an order would be rejected on-chain, it is rejected in simulation too. No false fills, no surprises. ✦ Going Live is one switch, and it asks for confirmation before any real funds move. Build it. Test it. Trade it. A full perps strategy, proven on paper before a single dollar moves. 30 operations in one node: ✦ Read live markets, order book depth, candles, and funding rates ✦ Track your positions, collateral, and PnL, realized and unrealized ✦ Place limit, market, and stop-loss orders, plus conditional triggers ✦ Cancel orders, manage margin, and move collateral, all from the workflow No scripts. No backend. No terminal to babysit. Just a workflow that trades. You can try it for free. Demo + Link down below 👇
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🔥 Phoenix is officially live on Solaris AI Flow. You can now trade Phoenix perps inside a Solaris AI workflow. No code. Drop a node onto the canvas, pick an operation, and wire it to anything: AI signals, price feeds, schedules, alerts. The full order-book DEX from Ellipsis Labs, now programmable. Built so you can trade with confidence: ✦ Paper mode is on by default. Every order is checked and simulated against the live order book, real depth and real slippage, but nothing is signed or broadcast. ✦ Paper behaves exactly like Live. If an order would be rejected on-chain, it is rejected in simulation too. No false fills, no surprises. ✦ Going Live is one switch, and it asks for confirmation before any real funds move. Build it. Test it. Trade it. A full perps strategy, proven on paper before a single dollar moves. 30 operations in one node: ✦ Read live markets, order book depth, candles, and funding rates ✦ Track your positions, collateral, and PnL, realized and unrealized ✦ Place limit, market, and stop-loss orders, plus conditional triggers ✦ Cancel orders, manage margin, and move collateral, all from the workflow No scripts. No backend. No terminal to babysit. Just a workflow that trades. You can try it for free. Demo + Link down below 👇

Solaris AI

10,075 görüntüleme • 3 ay önce