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Coding some WebGL shaders for 3D Gaussian Splatting 😀 Check the quality of clothes at 9 seconds! We are going to push things for fashion. live demo :

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Alexandre Devaux

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327,048 Aufrufe • vor 2 Jahren •via X (Twitter)

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We will be in ACM SIGGRAPH 2023 with "3D Gaussian Splatting for Real-Time Radiance Field Rendering", have you ever seen radiance fields with 100+ FPS and MipNeRF360 quality? Check out our website here:
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We will be in ACM SIGGRAPH 2023 with "3D Gaussian Splatting for Real-Time Radiance Field Rendering", have you ever seen radiance fields with 100+ FPS and MipNeRF360 quality? Check out our website here:

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I made a 3D Gaussian Splatting renderer for WebGL! The following scene renders 1.3M splats in real time. I wanted to understand a bit more how gaussian splats were rasterized, reimplementing the original paper seemed to be the best approach. I will publish it on github soon!
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I made a 3D Gaussian Splatting renderer for WebGL! The following scene renders 1.3M splats in real time. I wanted to understand a bit more how gaussian splats were rasterized, reimplementing the original paper seemed to be the best approach. I will publish it on github soon!

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Meet 3D Gaussian Splatting - a 3D AI breakthrough that’s changing the game for real-time 3D rendering. It generates 3D world with state-of-the-art visuals at fast speeds: 100+ fps at 1080p. Here’s the magic behind it:
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Meet 3D Gaussian Splatting - a 3D AI breakthrough that’s changing the game for real-time 3D rendering. It generates 3D world with state-of-the-art visuals at fast speeds: 100+ fps at 1080p. Here’s the magic behind it:

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Apple just trained a 3D Gaussian head reconstruction model on 10,000+ subjects. Feed-forward. No test-time optimization. New identity in, reconstructed Gaussian head out. The UV-parameterized Gaussian representation decouples the number of Gaussians from the number and resolution of input images, making it practical to train with many high resolution views. And the heads are not just static either: text-conditioned identity generation, plus blendshape-driven latent animation across identities. We've been building in the 3D Gaussian Splatting space for a while. The gap between "research demo" and "works on real people at scale" is closing fast.
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Apple just trained a 3D Gaussian head reconstruction model on 10,000+ subjects. Feed-forward. No test-time optimization. New identity in, reconstructed Gaussian head out. The UV-parameterized Gaussian representation decouples the number of Gaussians from the number and resolution of input images, making it practical to train with many high resolution views. And the heads are not just static either: text-conditioned identity generation, plus blendshape-driven latent animation across identities. We've been building in the 3D Gaussian Splatting space for a while. The gap between "research demo" and "works on real people at scale" is closing fast.

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DroneSplat: 3D Gaussian Splatting for Robust 3D Reconstruction from In-the-Wild Drone Imagery Abstract: Drones have become essential tools for reconstructing wild scenes due to their outstanding maneuverability. Recent advances in radiance field methods have achieved remarkable rendering quality, providing a new avenue for 3D reconstruction from drone imagery. However, dynamic distractors in wild environments challenge the static scene assumption in radiance fields, while limited view constraints hinder the accurate capture of underlying scene geometry. To address these challenges, we introduce DroneSplat, a novel framework designed for robust 3D reconstruction from in-the-wild drone imagery. Our method adaptively adjusts masking thresholds by integrating local-global segmentation heuristics with statistical approaches, enabling precise identification and elimination of dynamic distractors in static scenes. We enhance 3D Gaussian Splatting with multi-view stereo predictions and a voxel-guided optimization strategy, supporting high-quality rendering under limited view constraints. For comprehensive evaluation, we provide a drone-captured 3D reconstruction dataset encompassing both dynamic and static scenes. Extensive experiments demonstrate that DroneSplat outperforms both 3DGS and NeRF baselines in handling in-the-wild drone imagery.

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3D Gaussian Splatting for Real-Time Radiance Field Rendering paper page: Radiance Field methods have recently revolutionized novel-view synthesis of scenes captured with multiple photos or videos. However, achieving high visual quality still requires neural networks that are costly to train and render, while recent faster methods inevitably trade off speed for quality. For unbounded and complete scenes (rather than isolated objects) and 1080p resolution rendering, no current method can achieve real-time display rates. We introduce three key elements that allow us to achieve state-of-the-art visual quality while maintaining competitive training times and importantly allow high-quality real-time (>= 30 fps) novel-view synthesis at 1080p resolution. First, starting from sparse points produced during camera calibration, we represent the scene with 3D Gaussians that preserve desirable properties of continuous volumetric radiance fields for scene optimization while avoiding unnecessary computation in empty space; Second, we perform interleaved optimization/density control of the 3D Gaussians, notably optimizing anisotropic covariance to achieve an accurate representation of the scene; Third, we develop a fast visibility-aware rendering algorithm that supports anisotropic splatting and both accelerates training and allows realtime rendering. We demonstrate state-of-the-art visual quality and real-time rendering on several established datasets.
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Blossom → For our latest WebGL experiment our aim was to see how closely we could recreate this petal particle effect in real-time. We've spent waaay too long just playing with the demo - let us know what you think! #webgl #threejs #realtime #3d
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Blossom → For our latest WebGL experiment our aim was to see how closely we could recreate this petal particle effect in real-time. We've spent waaay too long just playing with the demo - let us know what you think! #webgl #threejs #realtime #3d

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*filling out a form* Taeyong: but for the option, buying clothes only when your clothes are worn out. this is quite chill.. i want to put a check on this option Johnny: but for Jaehyun, he wears clothes that are worn out as fashion... 😂
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*filling out a form* Taeyong: but for the option, buying clothes only when your clothes are worn out. this is quite chill.. i want to put a check on this option Johnny: but for Jaehyun, he wears clothes that are worn out as fashion... 😂

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Self-Calibrating Gaussian Splatting for Large Field of View Reconstruction Note: Check below for full video. Abstract (cited): "In this paper, we present a self-calibrating framework that jointly optimizes camera parameters, lens distortion, and 3D Gaussian representations, enabling accurate and efficient scene reconstruction. Our technique is particularly effective for high-quality scene reconstruction from large field-of-view (FOV) imagery taken with wide-angle lenses, allowing the scene to be modeled from a smaller number of images. We introduce a novel method for modeling complex lens distortions using a hybrid network that combines invertible residual networks with explicit grids. This design effectively regularizes the optimization process, achieving greater accuracy than conventional camera models. Additionally, we propose a cubemap-based resampling strategy to support large FOV images without sacrificing resolution or introducing distortion artifacts. Our method is compatible with the fast rasterization of Gaussian Splatting, adaptable to a wide variety of camera lens distortions, and demonstrates state-of-the-art performance on both synthetic and real-world datasets."

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RTX Play Live TODAY! At 1PM PT we will be live with Jakub Vambersky playing and chatting all things Gray Zone Warfare! Also, with some game codes to giveaway! Super excited for this one 😀 Today 4/24 at 1PM PT!
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RTX Play Live TODAY! At 1PM PT we will be live with Jakub Vambersky playing and chatting all things Gray Zone Warfare! Also, with some game codes to giveaway! Super excited for this one 😀 Today 4/24 at 1PM PT!

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🎉 MIDI will be presented at #CVPR2025! We’ve dropped the code + demo for everyone to play with. Now, with our MV-Adapter, you can also create textures for the generated 3D scenes. Check the code and demo below!

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The Quality of Life update and Easter event are now live on Public Test Branch, we can't wait for you to test them out!

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In the summer of 2023, I cold emailed Jensen Huang and asked to capture a NeRF of him at SIGGRAPH. He responded in about an hour and said yes. A radiance field is, in the simplest terms, akin to a 3D photograph. A moment in time, so completely reconstructed that you can move through it and see it from angles the original cameras never occupied. NeRFs were the original method. Gaussian splatting, which debuted at that same SIGGRAPH, has since become the dominant form of radiance field. I called my late friend James, who told me we needed to begin practicing immediately. We ran capture after capture for weeks until we consistently got the capture time down to ~30 seconds with one camera. Later, in a hallway at the LA Convention Center during SIGGRAPH, I captured the portrait you're seeing now, a full 360° gaussian splat of Jensen, rendered here as a 2D flythrough. Afterward, I continued the conversation with him and members of his team to make the case for radiance fields as a foundational representation for imaging. To my surprise, they listened. Three years later, NVIDIA has several works, including NuRec, fVDB, 3DGRUT, and gsplat all utilizing radiance fields. The landscape has evolved enough that the reasoning is obvious. Gaussian splatting has begun to ship across some of the world’s largest industries, including autonomous vehicles, AEC, geospatial, media and entertainment, robotics, e-commerce, hospitality. It’s become clear that lifelike 3D is here to stay. And yet I think we will look back and be disappointed by how late we started taking 3D portraits of the people around us, just like how we have sparse 2D photos of our grandparents and great grandparents. We have billions of photographs of the people we know and love, but almost no radiance fields of them. I'll be returning to SIGGRAPH in LA where this was initially captured three years ago, with the landscape looking significantly different. Radiance fields are more under deployed than ever relative to what they can do. I'm excited for the future of imaging, and for 2D to transition into 3D. I have a few things up my sleeve that I think will make that case plainly.
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In the summer of 2023, I cold emailed Jensen Huang and asked to capture a NeRF of him at SIGGRAPH. He responded in about an hour and said yes. A radiance field is, in the simplest terms, akin to a 3D photograph. A moment in time, so completely reconstructed that you can move through it and see it from angles the original cameras never occupied. NeRFs were the original method. Gaussian splatting, which debuted at that same SIGGRAPH, has since become the dominant form of radiance field. I called my late friend James, who told me we needed to begin practicing immediately. We ran capture after capture for weeks until we consistently got the capture time down to ~30 seconds with one camera. Later, in a hallway at the LA Convention Center during SIGGRAPH, I captured the portrait you're seeing now, a full 360° gaussian splat of Jensen, rendered here as a 2D flythrough. Afterward, I continued the conversation with him and members of his team to make the case for radiance fields as a foundational representation for imaging. To my surprise, they listened. Three years later, NVIDIA has several works, including NuRec, fVDB, 3DGRUT, and gsplat all utilizing radiance fields. The landscape has evolved enough that the reasoning is obvious. Gaussian splatting has begun to ship across some of the world’s largest industries, including autonomous vehicles, AEC, geospatial, media and entertainment, robotics, e-commerce, hospitality. It’s become clear that lifelike 3D is here to stay. And yet I think we will look back and be disappointed by how late we started taking 3D portraits of the people around us, just like how we have sparse 2D photos of our grandparents and great grandparents. We have billions of photographs of the people we know and love, but almost no radiance fields of them. I'll be returning to SIGGRAPH in LA where this was initially captured three years ago, with the landscape looking significantly different. Radiance fields are more under deployed than ever relative to what they can do. I'm excited for the future of imaging, and for 2D to transition into 3D. I have a few things up my sleeve that I think will make that case plainly.

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17,663 Aufrufe • vor 1 Monat

Ok, I think we did it? Yesterday was Unity, and today it's Godot. Would you like to see another die there? Remember to subscribe to Godot Shaders Bible here ⭐️ P.S.: Yes, we’re going to give this one away for free at some point. 🙌 #GodotEngine #godot #indiedev #gamedev #shaders
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Ok, I think we did it? Yesterday was Unity, and today it's Godot. Would you like to see another die there? Remember to subscribe to Godot Shaders Bible here ⭐️ P.S.: Yes, we’re going to give this one away for free at some point. 🙌 #GodotEngine #godot #indiedev #gamedev #shaders

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Thanks for the tweet. We improve 3D Gaussain splatting for dash cam videos that contain serious reflections and obstructions. With Dash cam videos, it's possible to leverage massive driving data. Visit our page at Codes will be soon.
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Thanks for the tweet. We improve 3D Gaussain splatting for dash cam videos that contain serious reflections and obstructions. With Dash cam videos, it's possible to leverage massive driving data. Visit our page at Codes will be soon.

Xiao-Xiao Long

44,444 Aufrufe • vor 2 Jahren

And it's live, the frontend still throttle to 250ms updates for now, just monitoring things. Will push the full speed later on after a few performance improvements in the code computing the full order books from Hyperliquid logs files. Was a good day of coding 🦈
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And it's live, the frontend still throttle to 250ms updates for now, just monitoring things. Will push the full speed later on after a few performance improvements in the code computing the full order books from Hyperliquid logs files. Was a good day of coding 🦈

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10,274 Aufrufe • vor 1 Monat