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

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.show more

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.show more

Official Launch of the MrNeRF 3DGS Bounty 2: We're... offering 🏆 $1600 + $500 bonus for improving initialization & training without densification for 3D Gaussian Splatting! RT & tag friends who might crush this. Details in thread 👇show more

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.show more

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 :show more

Tried the PBR Painter plugin for Blender to refine... my texturing and it's honestly great! Only the primitive texture painting engine of Blender is holding it back (e.g. brush size locked to screen space) Still a blessing not having to export to Substance for shader authoring.show more

Samantha Ryan, our VP of Content for Reality Labs,... shares what’s next for VR 👉 Tl;dr ➡️ We're putting developers at the center of VR’s next chapter. Worlds is going mobile-first. Two platforms, two paths. Both here for the long haul. Details ☝️show more

Enrico Labarile talked about the creation of Chapter 2... of the animated Mediterranea-vibe environment, detailing the modeling, texturing, and shading processes for the trucks and cliffs while emphasizing how storytelling was achieved. Read the interview:show more

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.show more

TL;DR of EDG vs FUT for those who missed... the matchshow more

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.show more

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.show more

SplatVoxel: History-Aware Novel View Streaming without Temporal Training Contributions:... • We propose a hybrid Splat-Voxel feed-forward reconstruction framework that leverages historical information to enable novel view streaming, without relying on multi-view video datasets for training. • We develop an efficient sparse voxel transformer with a coarse-to-fine voxel representation, outperforming existing feed-forward Gaussian splatting methods. • Experiment results demonstrate that our proposed framework enhances novel view synthesis for streaming scene reconstruction, providing better visual quality and reduced temporal artifacts through history-aware modeling.show more

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:show more

Is Google taking initial steps to enhance Street View?... For some reason, Street View seems stuck in technology that feels outdated. I wonder if we'll see such improvements on the product side. Also, note how much better it performs in all aspects compared to Zip-NeRF in their presented material. It offers more details and fewer artifacts. Great work! "LODGE: Level-of-Detail Large-Scale Gaussian Splatting with Efficient Rendering" Contributions: • We propose a novel LOD representation for 3DGS which, unlike previous methods [27, 28, 17], does not recompute the list of used Gaussians at each frame. This allows for acceleration and compaction, enabling the rendering of large-scale scenes even on mobile devices. • We design a strategy to automatically select optimal hyperparameters for splitting LODs, whereas most other methods require manual tuning of hyperparameters for each 3D scene. • To further accelerate rendering, we split the scene into chunks and pre-compute sets of active Gaussians per chunk. • Finally, we introduce a novel opacity interpolation scheme to produce visually pleasing rendering and eliminate artifacts when transitioning between chunks.show more

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.show more

📢 Automatic PBR : Image-to-material (I2M) 👉Textured Mesh in... > Full PBR Mesh out Our latest foundation model for enriching existing 3D assets with the full array of PBR materials, whilst maintaining the same mesh geometry and UV unwrap. #I2M #PBR #CV #Marso #texturing #gamedev #computervision M-XRshow more

Seeing my whole TL praising Tatum instead of hating... on him, I used to pray for times like this man 🥲🥲🥲show more

AI projects looking to build on the #superledger are... invited to apply for Wave 4 of the Coreum Grant Program. Harness the power of AI, Smart Tokens, & IBC Interoperability to bring your application to millions of crypto users worldwide. For details:show more