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splaTV, developed by Kevin Kwok, is a browser-based implementation for experiencing dynamic Gaussian Splatting with Spacetime Gaussians. This newly released application supports both WebGL and WebXR technologies and is available under the MIT License. 🔗

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Radiance Fields

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18,667 görüntüleme • 2 yıl önce •via X (Twitter)

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The first public dynamic Gaussian Splatting implementation in VR is here from San Francisco based Gmix, compatible with WebXR and Apple Vision Pro. 🔗
0:17

The first public dynamic Gaussian Splatting implementation in VR is here from San Francisco based Gmix, compatible with WebXR and Apple Vision Pro. 🔗

Radiance Fields

31,612 görüntüleme • 2 yıl önce

That's really cool. 4D Gaussian Splatting running in the browser by Gmix. Went somehow under the radar with the #Sora release.
0:16

That's really cool. 4D Gaussian Splatting running in the browser by Gmix. Went somehow under the radar with the #Sora release.

MrNeRF

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MoE-GS: Mixture of Experts for Dynamic Gaussian Splatting Contributions: • MoE-GS: the first dynamic Gaussian splatting framework employing a Mixture-of-Experts architecture, enabling robust and adaptive reconstruction across diverse dynamic scenes. • A novel Volume-aware Pixel Router integrates expert outputs through differentiable weight splatting, achieving spatially and temporally coherent adaptive blending. • Efficiency of MoE-GS is improved through single-pass multi-expert rendering and gate-aware Gaussian pruning. A separate knowledge distillation strategy trains individual experts with pseudo-labels from the MoE model, enhancing quality without modifying the architecture.
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MoE-GS: Mixture of Experts for Dynamic Gaussian Splatting Contributions: • MoE-GS: the first dynamic Gaussian splatting framework employing a Mixture-of-Experts architecture, enabling robust and adaptive reconstruction across diverse dynamic scenes. • A novel Volume-aware Pixel Router integrates expert outputs through differentiable weight splatting, achieving spatially and temporally coherent adaptive blending. • Efficiency of MoE-GS is improved through single-pass multi-expert rendering and gate-aware Gaussian pruning. A separate knowledge distillation strategy trains individual experts with pseudo-labels from the MoE model, enhancing quality without modifying the architecture.

MrNeRF

10,346 görüntüleme • 8 ay önce

Esri just brought gaussian splatting to the web. ArcGIS Maps SDK 5.0 introduces a native GaussianSplatLayer for SceneView. Splats now stream directly into browser-based GIS apps.
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Esri just brought gaussian splatting to the web. ArcGIS Maps SDK 5.0 introduces a native GaussianSplatLayer for SceneView. Splats now stream directly into browser-based GIS apps.

Radiance Fields

12,907 görüntüleme • 4 ay önce

Some personal news! 📣 Recently, I joined Niantic as the product lead to work on MR apps and Gaussian splatting! Today, we’re launching “Into The Scaniverse”—A way of viewing Scaniverse splats in VR (yours and the ones posted to the map) 📸 It’s available as a webxr app via Quest Browser (for Q3 and Q3S), soon to launch in the Meta Horizon store. Honored to be working with quite a lot of brilliant folks at Niantic 🙌 Link to the webxr app 👇
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Some personal news! 📣 Recently, I joined Niantic as the product lead to work on MR apps and Gaussian splatting! Today, we’re launching “Into The Scaniverse”—A way of viewing Scaniverse splats in VR (yours and the ones posted to the map) 📸 It’s available as a webxr app via Quest Browser (for Q3 and Q3S), soon to launch in the Meta Horizon store. Honored to be working with quite a lot of brilliant folks at Niantic 🙌 Link to the webxr app 👇

Azad Balabanian

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I implemented 3D Gaussian Splatting in WebGL. Check it out here:
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I implemented 3D Gaussian Splatting in WebGL. Check it out here:

Kevin Kwok

168,875 görüntüleme • 2 yıl önce

My C++ 3DGS implementation has transitioned to the gsplat backend and is now licensed under Apache 2.0. - Supports MCMC densification by default. - Includes a fused bilateral grid implementation. - A basic viewer, contributed by the community, is available with more features in development. - Runs in headless mode. Exciting plans are underway for the project's evolution over the sumner. Check it out!
0:15

My C++ 3DGS implementation has transitioned to the gsplat backend and is now licensed under Apache 2.0. - Supports MCMC densification by default. - Includes a fused bilateral grid implementation. - A basic viewer, contributed by the community, is available with more features in development. - Runs in headless mode. Exciting plans are underway for the project's evolution over the sumner. Check it out!

MrNeRF

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"Content-Aware Texturing for Gaussian Splatting" TL;DR: Texturing instead of millions of Gaussians for fine details; fixed texel size
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"Content-Aware Texturing for Gaussian Splatting" TL;DR: Texturing instead of millions of Gaussians for fine details; fixed texel size

Alexandre Morgand

34,511 görüntüleme • 6 ay önce

[SIGGRAPH ASIA '25] Detail-Enhanced Gaussian Splatting for Large-Scale Volumetric Capture Contributions: - A two-stage approach to performance capture, combining a scene-scale capture rig and a single-actor facial capture rig. - A novel high-quality scene-scale volumetric performance capture rig, incorporating both static and dynamic cameras to track the performance of multiple actors. - A reconstruction pipeline for dynamic performance capture, featuring stable calibration of moving cameras and 4DGS with improved dynamic range and color fidelity. - A detail enhancement Diffusion Model, which supports 4K, RGB, and Alpha, with improved temporal stability.
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[SIGGRAPH ASIA '25] Detail-Enhanced Gaussian Splatting for Large-Scale Volumetric Capture Contributions: - A two-stage approach to performance capture, combining a scene-scale capture rig and a single-actor facial capture rig. - A novel high-quality scene-scale volumetric performance capture rig, incorporating both static and dynamic cameras to track the performance of multiple actors. - A reconstruction pipeline for dynamic performance capture, featuring stable calibration of moving cameras and 4DGS with improved dynamic range and color fidelity. - A detail enhancement Diffusion Model, which supports 4K, RGB, and Alpha, with improved temporal stability.

MrNeRF

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Gaussian Head Avatar: Ultra High-fidelity Head Avatar via Dynamic Gaussians paper page: Creating high-fidelity 3D head avatars has always been a research hotspot, but there remains a great challenge under lightweight sparse view setups. In this paper, we propose Gaussian Head Avatar represented by controllable 3D Gaussians for high-fidelity head avatar modeling. We optimize the neutral 3D Gaussians and a fully learned MLP-based deformation field to capture complex expressions. The two parts benefit each other, thereby our method can model fine-grained dynamic details while ensuring expression accuracy. Furthermore, we devise a well-designed geometry-guided initialization strategy based on implicit SDF and Deep Marching Tetrahedra for the stability and convergence of the training procedure. Experiments show our approach outperforms other state-of-the-art sparse-view methods, achieving ultra high-fidelity rendering quality at 2K resolution even under exaggerated expressions.
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Gaussian Head Avatar: Ultra High-fidelity Head Avatar via Dynamic Gaussians paper page: Creating high-fidelity 3D head avatars has always been a research hotspot, but there remains a great challenge under lightweight sparse view setups. In this paper, we propose Gaussian Head Avatar represented by controllable 3D Gaussians for high-fidelity head avatar modeling. We optimize the neutral 3D Gaussians and a fully learned MLP-based deformation field to capture complex expressions. The two parts benefit each other, thereby our method can model fine-grained dynamic details while ensuring expression accuracy. Furthermore, we devise a well-designed geometry-guided initialization strategy based on implicit SDF and Deep Marching Tetrahedra for the stability and convergence of the training procedure. Experiments show our approach outperforms other state-of-the-art sparse-view methods, achieving ultra high-fidelity rendering quality at 2K resolution even under exaggerated expressions.

AK

65,834 görüntüleme • 2 yıl önce

GSTAR: Gaussian Surface Tracking and Reconstruction Contributions: • A new framework for tracking and reconstructing dynamic scenes, combining 3D Gaussians and meshes to effectively manage changes in topology. • A method for Gaussian unbinding and surface re-meshing, allowing for the generation of new surfaces as topologies evolve. • A method for handling large or fast deformations of surfaces between frames using scene flow warping. Abstract (excerpt): However, tracking dynamic surfaces with 3D Gaussians remains challenging due to complex topology changes, such as surfaces appearing, disappearing, or splitting. To address these challenges, we propose GSTAR, a novel method that achieves photo-realistic rendering, accurate surface reconstruction, and reliable 3D tracking for general dynamic scenes with changing topology. Given multi-view captures as input, GSTAR binds Gaussians to mesh faces to represent dynamic objects. For surfaces with consistent topology, GSTAR maintains the mesh topology and tracks the meshes using Gaussians.
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GSTAR: Gaussian Surface Tracking and Reconstruction Contributions: • A new framework for tracking and reconstructing dynamic scenes, combining 3D Gaussians and meshes to effectively manage changes in topology. • A method for Gaussian unbinding and surface re-meshing, allowing for the generation of new surfaces as topologies evolve. • A method for handling large or fast deformations of surfaces between frames using scene flow warping. Abstract (excerpt): However, tracking dynamic surfaces with 3D Gaussians remains challenging due to complex topology changes, such as surfaces appearing, disappearing, or splitting. To address these challenges, we propose GSTAR, a novel method that achieves photo-realistic rendering, accurate surface reconstruction, and reliable 3D tracking for general dynamic scenes with changing topology. Given multi-view captures as input, GSTAR binds Gaussians to mesh faces to represent dynamic objects. For surfaces with consistent topology, GSTAR maintains the mesh topology and tracks the meshes using Gaussians.

MrNeRF

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WildGS-SLAM: Monocular Gaussian Splatting SLAM in Dynamic Environments TL;DR: We present WildGS-SLAM, a robust monocular RGB SLAM system. - Utilizes uncertainty-aware tracking and mapping to handle dynamic scenes. - Leverages DINOv2-based uncertainty maps for dynamic object removal. - Improves tracking and mapping. - Enables high-quality view synthesis.
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WildGS-SLAM: Monocular Gaussian Splatting SLAM in Dynamic Environments TL;DR: We present WildGS-SLAM, a robust monocular RGB SLAM system. - Utilizes uncertainty-aware tracking and mapping to handle dynamic scenes. - Leverages DINOv2-based uncertainty maps for dynamic object removal. - Improves tracking and mapping. - Enables high-quality view synthesis.

MrNeRF

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Introducing pixelSplat: feed-forward Gaussian splats from image pairs! Led by David Charatan and Lester Li, collaborating with Andrea Tagliasacchi @CVPR! We propose a memory-efficient, fast and editable alternative to pixelNeRF based on 3D Gaussian Splatting! 1/n

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V-Ray is now available for free to Blender users under the new Community Edition license, suitable for both personal and commercial projects. Learn more and get it here:
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V-Ray is now available for free to Blender users under the new Community Edition license, suitable for both personal and commercial projects. Learn more and get it here:

80 LEVEL

43,108 görüntüleme • 2 ay önce

This new Spline feature (importing Gaussian Splatting) and portal card effect is a perfect match! You should try it!!
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This new Spline feature (importing Gaussian Splatting) and portal card effect is a perfect match! You should try it!!

Max

356,900 görüntüleme • 2 yıl önce

Adaptive and Temporally Consistent Gaussian Surfels for Multi-view Dynamic Reconstruction Contributions: • A method for efficiently reconstructing dynamic surfaces from multi-view videos using Gaussian surfels. • A unified and gradient-aware densification strategy for optimizing dynamic 3D Gaussians with fine details. • A temporal consistency approach that ensures stable and coherent surface reconstructions across frames by enforcing consistency on curvature maps. • Extensive experiments that demonstrate our method’s advantages including fast training, high-fidelity novel view synthesis, and accurate surface geometry.
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Adaptive and Temporally Consistent Gaussian Surfels for Multi-view Dynamic Reconstruction Contributions: • A method for efficiently reconstructing dynamic surfaces from multi-view videos using Gaussian surfels. • A unified and gradient-aware densification strategy for optimizing dynamic 3D Gaussians with fine details. • A temporal consistency approach that ensures stable and coherent surface reconstructions across frames by enforcing consistency on curvature maps. • Extensive experiments that demonstrate our method’s advantages including fast training, high-fidelity novel view synthesis, and accurate surface geometry.

MrNeRF

31,821 görüntüleme • 1 yıl önce

2/2 Explore a vision of the future created with #AI #webgl 🍃 🍃 Also available in #WebXR 🥽
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2/2 Explore a vision of the future created with #AI #webgl 🍃 🍃 Also available in #WebXR 🥽

Active Theory

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testing out Gaussian splats in mixed reality with WebXR and Three.js
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testing out Gaussian splats in mixed reality with WebXR and Three.js

dmvrg

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Gaussian splatting is getting crazy!
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Gaussian splatting is getting crazy!

Christopher Fryant

46,970 görüntüleme • 8 ay önce

I always thought camera pose estimation is necessary for 3D reconstruction, until Zequn and Stephen proved me wrong! Introducing PreF3R, purely feed-forward 3D Gaussian Splatting without any intermediate pose estimation and COLMAP initialization. Video in, 3D Gaussians and novel view rendering out. Key technique: spatial memory network from Spann3R and Gaussian head supervised by pointmap loss plus photometric loss. See more at:
0:19

I always thought camera pose estimation is necessary for 3D reconstruction, until Zequn and Stephen proved me wrong! Introducing PreF3R, purely feed-forward 3D Gaussian Splatting without any intermediate pose estimation and COLMAP initialization. Video in, 3D Gaussians and novel view rendering out. Key technique: spatial memory network from Spann3R and Gaussian head supervised by pointmap loss plus photometric loss. See more at:

Heng Yang

20,160 görüntüleme • 1 yıl önce