LetsGo: Large-Scale Garage Modeling and Rendering via LiDAR-Assisted Gaussian Primitives

arXiv:2404.09748v1 Announce Type: new
Abstract: Large garages are ubiquitous yet intricate scenes in our daily lives, posing challenges characterized by monotonous colors, repetitive patterns, reflective surfaces, and transparent vehicle glass. Conventional Structure from Motion (SfM) methods for camera pose estimation and 3D reconstruction fail in these environments due to poor correspondence construction. To address these challenges, this paper introduces LetsGo, a LiDAR-assisted Gaussian splatting approach for large-scale garage modeling and rendering. We develop a handheld scanner, Polar, equipped with IMU, …

3d reconstruction abstract arxiv challenges colors cs.cv cs.gr daily environments glass lidar modeling patterns rendering scale transparent type via