Image to Point Cloud Registration

Image-to-point cloud registration (I2P) aims to determine the relative pose (position and orientation) of a camera given an image and a 3D point cloud, crucial for tasks like robot localization and augmented reality. Recent research focuses on improving accuracy and efficiency by developing novel deep learning architectures, including transformer-based networks, reinforcement learning agents, and matching-free approaches that leverage cost volumes or pretrained diffusion models to establish robust 2D-3D correspondences. These advancements are driving progress in autonomous driving, robotics, and 3D scene reconstruction by enabling more accurate and reliable fusion of image and LiDAR data.