3 accepted papers
This work addresses the problem of active 3D mapping, where an agent must find an efficient trajectory to exhaustively reconstruct a new scene. Previous approaches mainly predict the next best view near the agent's location, which is prone to getting stuck in local areas. Additionally, existing indo…
Research in 3D mapping is crucial for smart city applications, yet the cost of acquiring 3D data often hinders progress. Visual localization, particularly monocular camera position estimation, offers a solution by determining the camera's pose solely through visual cues. However, this task is challe…
Some recent visual-based relocalization algorithms rely on deep learning methods to perform camera pose regression from image data. This letter focuses on the loss functions that embed the error between two poses to perform deep learning based camera pose regression. Existing loss functions are eith