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🏀 I built this PoC using a single 2D broadcast video: applied pitch detection, player positioning, and movement tracking to reconstruct the play in 3D and map it onto a real basketball court in XR.

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Stijn Spanhove

4,177 subscribers

36,895 görüntüleme • 7 ay önce •via X (Twitter)

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AI BASKETBALL ANALYSIS. A FULL COMPUTER VISION SYSTEM. BUILT ON YOLO, OPENCV, AND PYTHON. Take any NBA broadcast. Any camera angle. Any resolution. Feed it into the system. YOLO finds every player and the ball. Frame by frame. No manual annotation. No pre-labeled data.The model just sees the court and understands it. Zero-shot classification looks at jersey pixels and decides who plays for whom. Two teams separated in milliseconds. Without ever being told the team names. But here's where it gets wild. Court keypoint detection identifies the geometry of the playing surface. Homography transforms the broadcast camera into a top-down tactical map. Real meters. Real coordinates. From a flat 2D video. Now every player has a position on a real court. Every movement becomes a data point. Every pass becomes a vector. Speed. Distance. Possession time. Pass networks. All extracted from nothing but pixels. No GPS. No chips in the ball. No million-dollar Second Spectrum setup. A Python script and a GPU. The full pipeline is open source. The tutorial walks through every line of code. From detection to transformation to analytics output. Teams used to pay six figures for this data. Now you build it in an afternoon. Computer vision didn't just enter basketball. It democratized it.
5:58:26

AI BASKETBALL ANALYSIS. A FULL COMPUTER VISION SYSTEM. BUILT ON YOLO, OPENCV, AND PYTHON. Take any NBA broadcast. Any camera angle. Any resolution. Feed it into the system. YOLO finds every player and the ball. Frame by frame. No manual annotation. No pre-labeled data.The model just sees the court and understands it. Zero-shot classification looks at jersey pixels and decides who plays for whom. Two teams separated in milliseconds. Without ever being told the team names. But here's where it gets wild. Court keypoint detection identifies the geometry of the playing surface. Homography transforms the broadcast camera into a top-down tactical map. Real meters. Real coordinates. From a flat 2D video. Now every player has a position on a real court. Every movement becomes a data point. Every pass becomes a vector. Speed. Distance. Possession time. Pass networks. All extracted from nothing but pixels. No GPS. No chips in the ball. No million-dollar Second Spectrum setup. A Python script and a GPU. The full pipeline is open source. The tutorial walks through every line of code. From detection to transformation to analytics output. Teams used to pay six figures for this data. Now you build it in an afternoon. Computer vision didn't just enter basketball. It democratized it.

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🕹️ Turning drawings into XR worlds you can play in. I built a POC for Spectacles that turns imagination into reality. My niece drew a picture and with the help of Mirage 2, I brought it to life in an interactive environment.
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🕹️ Turning drawings into XR worlds you can play in. I built a POC for Spectacles that turns imagination into reality. My niece drew a picture and with the help of Mirage 2, I brought it to life in an interactive environment.

Stijn Spanhove

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🥳 NEW TUTORIAL 🥳 2D look is making a big come back and I love it! In this video I give you my tips to achieve convincing 2D look for your 3D animation using #Blender obviously 🤗 👉 #b3D #animation #p2dessign #2D #3D #anime
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🥳 NEW TUTORIAL 🥳 2D look is making a big come back and I love it! In this video I give you my tips to achieve convincing 2D look for your 3D animation using #Blender obviously 🤗 👉 #b3D #animation #p2dessign #2D #3D #anime

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I recreated the #ArcaneSeason2 Piltover Garden scene using #Blender. I roughly built a 3D scene, made a draft render, and then painted over it in 2D. All moving parts like foliage, characters and spinner are 3D elements. Breakdown coming soon. More info:

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Combining 2D and 3D in After Effects. In Foldspace, not every surface needs to be bent. Keep one flat for 2D artwork, and let the others exist in 3D space. This allows you to combine 2D and 3D objects in a single animation with no masks or tricks needed.
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Combining 2D and 3D in After Effects. In Foldspace, not every surface needs to be bent. Keep one flat for 2D artwork, and let the others exist in 3D space. This allows you to combine 2D and 3D objects in a single animation with no masks or tricks needed.

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The NHL partnered with Disney to broadcast its first-ever game in 3D animation yesterday. The broadcast used tracking chips embedded within the puck and player jerseys to recreate a real-time animated version of the game on Disney Channel. Pretty cool 🤯
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The NHL partnered with Disney to broadcast its first-ever game in 3D animation yesterday. The broadcast used tracking chips embedded within the puck and player jerseys to recreate a real-time animated version of the game on Disney Channel. Pretty cool 🤯

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The NBA app on Apple Vision Pro just dropped a massive update. World View (Alpha) puts you inside a live 3D recreation of the game. Every player and ref tracked in real time, rendered in NBA city-inspired environments, with visual effects when buckets drop or shots clank off the rim. You can move around the court using waypoints and even pull up the live broadcast synced to the 3D recreation simultaneously. The models aren’t photorealistic yet, but the tracking is impressively accurate. When they start mapping real likenesses onto these, it’s going to be something else entirely. Lastly, Tabletop is now called Court View. The NBA keeps pushing spatial computing forward. I love to see it!
0:40

The NBA app on Apple Vision Pro just dropped a massive update. World View (Alpha) puts you inside a live 3D recreation of the game. Every player and ref tracked in real time, rendered in NBA city-inspired environments, with visual effects when buckets drop or shots clank off the rim. You can move around the court using waypoints and even pull up the live broadcast synced to the 3D recreation simultaneously. The models aren’t photorealistic yet, but the tracking is impressively accurate. When they start mapping real likenesses onto these, it’s going to be something else entirely. Lastly, Tabletop is now called Court View. The NBA keeps pushing spatial computing forward. I love to see it!

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I got a lot of questions yesterday on how this made and if it was 3D or 2D so I decided to make a small breakdown video to explain. It was created using Non-Photorealistic Shaders and adapting a 2D animation workflow into 3D within Blender itself.
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I got a lot of questions yesterday on how this made and if it was 3D or 2D so I decided to make a small breakdown video to explain. It was created using Non-Photorealistic Shaders and adapting a 2D animation workflow into 3D within Blender itself.

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There is a game coming out where you have to play it in 2d and 3d at the same time
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There is a game coming out where you have to play it in 2d and 3d at the same time

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I built a full 3D strategy game with Opus 4.8 + Fable 5 Launching it today. Runs in your browser, no install, free: > 21 battlefields > economy + tech tree > tanks vs jets vs turrets, real counters > single player vs up to 7 AI bots > a battle royale storm map Click and you're at war in 10 seconds 👇

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Magic123: One Image to High-Quality 3D Object Generation Using Both 2D and 3D Diffusion Priors paper page: present Magic123, a two-stage coarse-to-fine approach for high-quality, textured 3D meshes generation from a single unposed image in the wild using both2D and 3D priors. In the first stage, we optimize a neural radiance field to produce a coarse geometry. In the second stage, we adopt a memory-efficient differentiable mesh representation to yield a high-resolution mesh with a visually appealing texture. In both stages, the 3D content is learned through reference view supervision and novel views guided by a combination of 2D and 3D diffusion priors. We introduce a single trade-off parameter between the 2D and 3D priors to control exploration (more imaginative) and exploitation (more precise) of the generated geometry. Additionally, we employ textual inversion and monocular depth regularization to encourage consistent appearances across views and to prevent degenerate solutions, respectively. Magic123 demonstrates a significant improvement over previous image-to-3D techniques, as validated through extensive experiments on synthetic benchmarks and diverse real-world images.

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Samsung Galaxy XR does have IR illuminators built into the HMD, just like Vision Pro So you can still interact with everything using hand tracking even while in pitch black darkness

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Today’s hobby project: Prototyped a real-time room scanning system with live sharing to XR devices. Explore scanned spaces in 3D on XR (not flat 2D screens) and share them with remote users for spatial remote collaboration. #metaquest #augmentedreality

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🛡#Live3D #Live2D #Live2DWIP🛡 Collaborating with Moshie Studio ✦ Live2D & Stream Assets , I built this pseudo-3D hand entirely in Live2D It supports full 360° X-axis rotation, finger grasping, and a fake outline effect. So in a way… this is a pseudo-2D inside pseudo-3D inside 2D ☝🤓

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