Recent advancements in 3D Gaussian Splatting (3DGS) are making significant strides in the field of 3D reconstruction and rendering. Researchers have introduced several innovative methods to enhance the efficiency and quality of 3DGS. The '3D Gaussian Splatting with Deferred Reflection' (3DGS-DR) aims to accommodate consumer-level GPUs with shorter training times. New York University's Grendel, a distributed system by H Zhao, H Weng, D Lu, and A Li, scales up 3DGS training across multiple GPUs. The RTG-SLAM technique offers real-time 3D reconstruction at twice the speed and half the memory cost of current methods using an RGBD camera. GS-ROR focuses on reflective object relighting via SDF priors, while SpotlessSplats is designed to ignore transient distractors using pre-trained features. Additionally, Lightweight Predictive 3D Gaussian Splats significantly reduces hard drive footprint while maintaining or improving quality. Lastly, RTGS enables real-time Gaussian Splatting on mobile devices through efficiency-guided pruning and foveated rendering.
RTGS: Enabling Real-Time Gaussian Splatting on Mobile Devices Using Efficiency-Guided Pruning and Foveated Rendering. https://t.co/Su8cfTu6bQ
[CV] SpotlessSplats: Ignoring Distractors in 3D Gaussian Splatting https://t.co/Eg9LqQKKxp - The paper presents SpotlessSplats, an approach to enable 3D Gaussian Splatting (3DGS) to reconstruct real-world scenes with transient distractors. - Current 3DGS methods requireโฆ https://t.co/nkjEhB5U43
๐จSpotLessSplats: Ignoring Distractors in 3D Gaussian Splatting ๐๐๐ซ๐จ๐ฃ: https://t.co/fGlgMlRLDs ๐๐๐๐ฌ: https://t.co/sp3FClkuXP Leverages pre-trained and general-purpose features coupled with robust optimization to effectively ignore transient distractors. https://t.co/pkNG6tc2i0
Recent approaches representing 3D objects and scenes using Gaussian splats show increased rendering speed across a variety of platforms and devices. While rendering such representations is indeed extremely efficient, storing and transmitting them is often prohibitively expensive.โฆ https://t.co/ELl4Bv4kX7
๐จLightweight Predictive 3D Gaussian Splats ๐๐๐ซ๐จ๐ฃ: https://t.co/ENEUs21vXd ๐๐๐๐ฌ: https://t.co/lCAiQpnNlb A new representation that dramatically reduces the hard drive footprint while featuring similar or improved quality compared to standard 3D Gaussian splats. https://t.co/OuxoQoWCuI
๐ข๐ข๐ข Introducing "๐๐ฉ๐จ๐ญ๐๐๐ฌ๐ฌ๐๐ฉ๐ฅ๐๐ญ๐ฌ: Ignoring Distractors in 3D Gaussian Splatting" lead by @sabour_sara and @lily_goli TL;DR: exploit pre-trained features to "recognize" what should be ignored. https://t.co/tSriCCEGqo Source code will be released in a few days. https://t.co/MGZX2ZZK7j
Lightweight Predictive 3D Gaussian Splats. https://t.co/bKA27KvzE5
SpotlessSplats: Ignoring Distractors in 3D Gaussian Splatting https://t.co/VedKtnZ3I1 Project: https://t.co/4YXt56GbfB Method โฌ๏ธ 1 I 2 https://t.co/YwMmAXk8iZ
Zhu et al. GS-ROR: 3D Gaussian Splatting for Reflective Object Relighting via SDF Priors https://t.co/zCn8LDUmfZ https://t.co/xnHnEfrO7E
GS-ROR: 3D Gaussian Splatting for Reflective Object Relighting via SDF Priors. https://t.co/BWHEx3qyqM
GS-ROR: 3D Gaussian Splatting for Reflective Object Relighting via SDF Priors https://t.co/1KCCQC07yY https://t.co/Tn3U36Rfle
Introducing RTG-SLAM: Real-time 3D Reconstruction at Scale Using Gaussian Splatting! ๐ Using Gaussian splatting with an RGBD camera, it offers high-quality reconstructions at twice the speed and half the memory cost of current methods. ๐ https://t.co/xWKzkIP29l https://t.co/hr1zFrPHS3
[CV] On Scaling Up 3D Gaussian Splatting Training H Zhao, H Weng, D Lu, A Li... [New York University] (2024) https://t.co/FIXdNfeyQQ - The paper introduces Grendel, a distributed system for training 3D Gaussian Splatting (3DGS) across multiple GPUs. 3DGS represents scenes usingโฆ https://t.co/jHKpyuEuUB
Reflections have been a hot topic in Radiance Field research lately. 3D Gaussian Splatting with Deferred Reflection or 3DGS-DR takes on this challenge, but accommodates consumer level GPUs and relatively short training times. Article: https://t.co/OQMaBUZd4S Project Page:โฆ https://t.co/RRQRw0Mpv5