Keskeiset käsitteet
Large receptive field and feature extraction strategies are crucial for enhancing 3D object detection in autonomous driving systems.
Tilastot
"Experiments on the KITTI dataset demonstrate that our approach significantly improves performance while maintaining a faster detection speed."
"The incorporation of DFFM enhances the overall 3D mAP performance of the SECOND by 0.71% and the VoxelNext network by an astonishing 2.12%."
Lainaukset
"Our contributions can be summarized as follows: Introduction of the DFFM to address the computational challenges associated with an expanding receptive field, enhancing overall model optimization."
"Proposal of a plug-and-play FSM designed to eliminate non-essential features, enabling the detector to concentrate on fitting crucial features."