在InstantSplat框架中,得到一个全局一致的3D表示涉及到几个关键步骤,这些步骤结合了端到端的密集立体模型(DUSt3R)和3D高斯喷涂(3D Gaussian Splatting)技术。以下是这个过程的概述:1)粗略几何初始化(Coarse Geometric Initialization):使用DUSt3R模型,该模型接受一对立体图像作为输入,并输出每个像素对应的3D点图和置信...
1.3D Gaussian Splatting: 2.深度正则化: 3.硬深度和软深度正则化: 4.全局-局部深度归一化: 5.神经颜色渲染器: 6.训练细节: 结论 CVPR2024论文合集链接: 论文标题 DNGaussian: Optimizing Sparse-View 3D Gaussian Radiance Fields with Global-Local Depth Normalization DNGaussian:使用全局-局部深度归一化...
3D Gaussian Splatting (3DGS) creates a radiance field consisting of 3D Gaussians to represent a scene. With sparse training views, 3DGS easily suffers from overfitting, negatively impacting rendering. This paper introduces a new co-regularization perspective for improving sparse-view 3DGS. When ...
文章结构展示了InstantSplat方法的设计、实现和评估，通过对比实验和消融研究，证明了其在处理稀疏视图和无姿态条件下的新视图合成任务中的有效性和优越性。InstantSplat为3D计算机视觉领域提供了一个强大的工具，特别是在需要快速且高质量渲染新视图的应用场景中。新视图合成方法的初始步骤是快速建立场景的粗略...
3D Gaussian Splatting (3DGS) has emerged as a promising approach for 3D scene representation, offering a reduction in computational overhead compared to Neural Radiance Fields (NeRF). However, 3DGS is susceptible to high-frequency artifacts and demonstrates suboptimal performance under sparse viewpoint...
InstantSplat: Sparse-view SfM-free Gaussian Splatting in Seconds This repository is the official implementation of InstantSplat, an sparse-view, SfM-free framework for large-scale scene reconstruction method using Gaussian Splatting. InstantSplat supports 3D-GS, 2D-GS, and Mip-Splatting. Table...
SparseGS: Real-Time 360° Sparse View Synthesis using Gaussian Splatting Environment Setups Conda environment: conda env create --file environment.yml conda activate SparseGS We suggest usingCUDA 12but CUDA 11 should work. You may need to change the cudatoolkit and pytorch version in the .yml...
三维视觉:三维重建、NeRF、3D Gaussian Splatting技术交流群; 自动驾驶仿真:Carla仿真、Autoware仿真等技术交流群; 自动驾驶开发:自动驾驶开发、ROS等技术交流群; 其它方向:自动标注与数据闭环、产品经理、硬件选型、求职面试、自动驾驶测试等技术交流群; 扫码添加汽车人助理微信邀请入群,备注:学校/公司+方向+昵称(快速...
三维视觉:三维重建、NeRF、3D Gaussian Splatting技术交流群; 自动驾驶仿真:Carla仿真、Autoware仿真等技术交流群; 自动驾驶开发:自动驾驶开发、ROS等技术交流群; 其它方向:自动标注与数据闭环、产品经理、硬件选型、求职面试、自动驾驶测试等技术交流群; 扫码添加汽车人助理微信邀请入群,备注:学校/公司+方向+昵称(快速...
3.3. Objective Function We apply the Gaussian focal loss [24] to the initialized queries of both modalities, given by Linit = LGF ocal(Yˆ L, YL) + LGF ocal(Yˆ C , YC ), (3) where Yˆ L, Yˆ C are the dense predictions ...