LiDARFormer: A Unified Transformer-based Multi-task Network for LiDAR Perception

arXiv:2303.12194v2 Announce Type: replace
Abstract: There is a recent trend in the LiDAR perception field towards unifying multiple tasks in a single strong network with improved performance, as opposed to using separate networks for each task. In this paper, we introduce a new LiDAR multi-task learning paradigm based on the transformer. The proposed LiDARFormer utilizes cross-space global contextual feature information and exploits cross-task synergy to boost the performance of LiDAR perception tasks across multiple large-scale datasets and benchmarks. Our novel …

abstract arxiv cs.cv lidar multiple multi-task learning network networks paper paradigm perception performance tasks transformer trend type