3 accepted papers
Visual localization is a fundamental machine learning problem. Absolute Pose Regression (APR) trains a scene-dependent model to efficiently map an input image to the camera pose in a pre-defined scene. However, many applications have continually changing environments, where inference data at novel p…
We focus on the domain adaptation problem for 3D semantic segmentation, addressing the challenge of data variability in point clouds collected by different LiDARs. Existing benchmarks often mix different types of datasets, which blurs and complicates segmentation evaluations. Here, we introduce a Mu…
LiDAR localization is a fundamental task in robotics and computer vision which estimates the pose of a LiDAR point cloud within a global map. Scene Coordinate Regression (SCR) has demonstrated state-of-the-art performance in this task. In SCR a scene is represented as a neural network which outputs…