With the advent of advanced multi-sensor fusion models, there has been a notable enhancement in the performance of perception tasks within in terms of autonomous driving. Despite these advancements, the challenges persist, particularly in the fusion of data from cameras and LiDAR sensors. A critial concern is the accurate alignment of data from these disparate sensors. Our observations indicate that the projected positions of LiDAR points often misalign on the corresponding image. Furthermore, fusion models appear to struggle in accurately segmenting these misaligned points. In this paper, we would like to address this problem carefully, with a specific focus on the nuScenes dataset and the SOTA of fusion models 2DPASS, and providing the possible solutions or potential improvements.

翻译：随着先进多传感器融合模型的出现，自动驾驶感知任务的性能得到了显著提升。尽管取得这些进展，挑战依然存在，特别是在相机与激光雷达传感器的数据融合方面。一个关键问题是这些异构传感器数据的精确对齐。我们的观察表明，激光雷达点的投影位置在对应图像上常出现错位。此外，融合模型在准确分割这些错位点时似乎存在困难。在本文中，我们致力于深入解决这一问题，重点关注nuScenes数据集及当前最优融合模型2DPASS，并提出可能的解决方案或潜在改进方向。