3 accepted papers
Previous benchmarks for evaluating large language models (LLMs) have primarily emphasized quantitative metrics, such as data volume. However, this focus may neglect key qualitative data attributes that can significantly impact the final rankings of LLMs, resulting in unreliable leaderboards. In this…
Point cloud classification and segmentation are fundamental tasks in 3D computer vision. Recently, deep learning-based methods, particularly 3D Transformers, have demonstrated their effectiveness across a variety of point cloud tasks. However, transformer-based methods embed position information int
In this paper, we propose a simple method, termed TWO, of directly closing the loop for LiDAR odometry. TWO suggests assigning high weights to the LIDAR observations corresponding to the old parts of the map; since these parts are built with the low-drift poses from the early odometry and can help d…