RGBD-3DGS-SLAM is a monocular SLAM system leveraging 3D Gaussian Splatting (3DGS) for accurate point cloud and visual odometry estimation. By integrating neural networks, it estimates depth and camera intrinsics from RGB images alone, with optional support for additional camera information and depth maps.

👾 A collection of code of depth estimation using light field data.

(3DV 2021) A High-fidelity 128-channel LiDAR Dataset with Panoramic Ambient and Reflectivity Imagery for Multi-modal Autonomous Driving Applications

Calculate fastq reads and sequencing coverage

a streamlined pipeline for converting videos into 3D Gaussian Splatting models

Scripts for downloading popular depth estimation datasets, including KITTI, DIODE, SUNRGBD, and soon NYUv2 and Make3D. This tool helps automate the download and organization of RGB images and corresponding depth maps, crucial for deep learning and computer vision research