COLMAP-free 3D Gaussian Splatting (3D-GS) has recently attracted increasing attention due to its remarkable performance in reconstructing high-quality 3D scenes from unposed images or videos. However, it often struggles to handle scenes with complex camera trajectories as featured by drastic rotation and translation across adjacent camera views, leading to degraded estimation of camera poses and further local minima in joint optimization of camera poses and 3D-GS. We propose PCR-GS, an innovative COLMAP-free 3DGS technique that achieves superior 3D scene modeling and camera pose estimation via camera pose co-regularization. PCR-GS achieves regularization from two perspectives. The first is feature reprojection regularization which extracts view-robust DINO features from adjacent camera views and aligns their semantic information for camera pose regularization. The second is wavelet-based frequency regularization which exploits discrepancy in high-frequency details to further optimize the rotation matrix in camera poses. Extensive experiments over multiple real-world scenes show that the proposed PCR-GS achieves superior pose-free 3D-GS scene modeling under dramatic changes of camera trajectories.
JOGS: Joint Optimization of Pose Estimation and 3D Gaussian Splatting
Key Laboratory of Big Data & Artificial Intelligence in Transportation (Beijing Jiaotong University), Ministry of Education, China（大数据与人工智能在交通中的关键实验室（北京交通大学），教育部，中国）；School of Computer Science and Technology, Beijing Jiaotong University（计算机科学与技术学院，北京交通大学）；Department of Artificial Intelligence, Westlake University（人工智能系，西湖大学）
Comparative evaluation of photogrammetric reconstruction methods and 3D Gaussian Splatting for road surface roughness analysis
School of International Education, Hubei University of Technology（湖北工业大学国际教育学院）；School of Computer Science, Hubei University of Technology（湖北工业大学计算机科学学院）
Robust and High-Fidelity 3D Gaussian Splatting: Fusing Pose Priors and Geometry Constraints for Texture-Deficient Outdoor Scenes
School of Mechatronical Engineering, Beijing Institute of Technology（机械电子工程学院，北京理工大学）；Beiing National Research Center for Information Science and Technology（北京国家信息科学与技术研究中心）；Qiyuan Lab（启元实验室）；Peking University（北京大学）
Geometric-Photometric Event-based 3D Gaussian Ray Tracing
Keio University（庆应义塾大学）；Technische Universität Berlin（柏林工业大学）；Science of Intelligence Excellence Cluster（智能科学卓越集群）；Einstein Center Digital Future（爱因斯坦数字未来中心）；Robotics Institute Germany（德国机器人研究所）；The University of Tokyo（东京大学）
