arXiv:2412.07608v3 Announce Type: replace 
Abstract: 3D Gaussian Splatting (3DGS) has emerged as a powerful technique for novel view synthesis, demonstrating remarkable capability in high-fidelity scene reconstruction through its Gaussian primitive representations. However, the computational overhead induced by the massive number of primitives poses a significant bottleneck to training efficiency. To overcome this challenge, we propose Group Training, a simple yet effective strategy that organizes Gaussian primitives into manageable groups, optimizing training efficiency and improving rendering quality. This approach shows universal compatibility with existing 3DGS frameworks, including vanilla 3DGS and Mip-Splatting, consistently achieving accelerated training while maintaining superior synthesis quality. Extensive experiments reveal that our straightforward Group Training strategy achieves up to 30\% faster convergence and improved rendering quality across diverse scenarios. Project Website: https://chengbo-wang.github.io/3DGS-with-Group-Training/

تم تقديم نهج جديد يسمى التدريب الجماعي لتحسين كفاءة تقنية 3D Gaussian Splatting (3DGS)، المعروفة بإعادة بناء المشاهد عالية الدقة. تنظم هذه الطريقة البدائل الغاوسية في مجموعات، مما يحسن بشكل كبير من سرعة التدريب وجودة العرض، حيث تحقق حتى 30% من التقارب الأسرع في سيناريوهات متنوعة.

Se ha introducido un nuevo enfoque llamado Group Training para mejorar la eficiencia del 3D Gaussian Splatting (3DGS), una técnica conocida por su reconstrucción de escenas de alta fidelidad. Este método organiza las primitivas gaussianas en grupos, mejorando significativamente la velocidad de entrenamiento y la calidad de renderizado, logrando hasta un 30% de convergencia más rápida en diversos escenarios.

Une nouvelle approche appelée Group Training a été introduite pour améliorer l'efficacité du 3D Gaussian Splatting (3DGS), une technique reconnue pour sa reconstruction de scènes haute fidélité. Cette méthode organise les primitives gaussiennes en groupes, améliorant considérablement la vitesse d'entraînement et la qualité de rendu, atteignant jusqu'à 30 % de convergence plus rapide dans divers scénarios.

A new approach called Group Training has been introduced to enhance the efficiency of 3D Gaussian Splatting (3DGS), a technique known for its high-fidelity scene reconstruction. This method organizes Gaussian primitives into groups, significantly improving training speed and rendering quality, achieving up to 30% faster convergence in various scenarios.

Faster and Better 3D Splatting via Group Training

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