RESUMEN
Recently, perception task based on Bird's-Eye View (BEV) representation has drawn more and more attention, and BEV representation is promising as the foundation for next-generation Autonomous Vehicle (AV) perception. However, most existing BEV solutions either require considerable resources to execute on-vehicle inference or suffer from modest performance. This paper proposes a simple yet effective framework, termed Fast-BEV, which is capable of performing faster BEV perception on the on-vehicle chips. Towards this goal, we first empirically find that the BEV representation can be sufficiently powerful without expensive transformer based transformation nor depth representation. Our Fast-BEV consists of five parts, We innovatively propose (1) a lightweight deploymentfriendly view transformation which fast transfers 2D image feature to 3D voxel space, (2) an multi-scale image encoder which leverages multi-scale information for better performance, (3) an efficient BEV encoder which is particularly designed to speed up on-vehicle inference. We further introduce (4) a strong data augmentation strategy for both image and BEV space to avoid over-fitting, (5) a multiframe feature fusion mechanism to leverage the temporal information. Among them, (1) and (3) enable Fast-BEV to be fast inference and deployment friendly on the on-vehicle chips, (2), (4) and (5) ensure that Fast-BEV has competitive performance. All these make Fast-BEV a solution with high performance, fast inference speed, and deployment-friendly on the on-vehicle chips of autonomous driving. Through experiments, on 2080Ti platform, our R50 model can run 52.6 FPS with 47.3% NDS on the nuScenes validation set, exceeding the 41.3 FPS and 47.5% NDS of the BEVDepth-R50 model [1] and 30.2 FPS and 45.7% NDS of the BEVDet4D-R50 model [2]. Our largest model (R101@900x1600) establishes a competitive 53.5% NDS on the nuScenes validation set. We further develop a benchmark with considerable accuracy and efficiency on current popular on-vehicle chips. The code is released at: https://github.com/Sense-GVT/FastBEV.
RESUMEN
To enhance the superatom family, the new superatom analogue Be11 of group IVA elements has been developed. Be11 can exhibit multiple valence states (+2 and +4), similar to carbon-group elements, and is capable of forming stable ionic compounds with other atoms such as carbon, chalcogen, (super)halogen, and hydroxyl. This resembles how tin and lead atoms combine with these elements to form stable molecules. Their special stability can be rationalized from the perspective of a cluster shell model. Sn or Pb could be the nearest atomic analogue to Be11 in group IVA, as the +2 oxidation state is more stable than the +4 oxidation state. This comparative investigation highlights the resemblance between Be11 and carbon-group elements, which encourages additional exploration within the superatom family.