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Traditional 3D object detection methods in Cartesian coordinate systems often overlook the symmetry and continuity of the target from different perspectives to some extent during camera image encoding due to the fixed wedgeshaped imaging geometry of invehicle cameras. To address this, in this paper, PolarDet, an innovative endtoend 3D object detection method in polar coordinates based on position and semantic information weighting is proposed. This method generates BEV (Bird's Eye View) position and semantic information in polar coordinates through polar coordinate queries and predefined polar grid, which then interacts with the BEV information from the previous frame to incorporate temporal information. When outputting the final detection results, PolarDet performs a weighted sum of position and semantic information to enhance information utilization efficiency, allowing the network to achieve higher detection accuracy. Extensive experiments on the challenging BEV object detection nuScenes dataset show that the optimal model of PolarDet achieves a mAP (mean average precision) of 0.469 and an NDS (nuScenes detection score) of 0.56, significantly outperforming Cartesian coordinatebased BEV detection methods.
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| 科 Family | 属数 Number of genus | 种数 Number of species | 占总种数比例 Percentage of total species (%) | 属 Genus | 种数 Number of species | 占总种数比例 Percentage of total species (%) |
|---|---|---|---|---|---|---|
| 鹅膏菌科Amanitaceae | 2 | 11 | 5.26 | 鹅膏菌属 Amanita | 10 | 4.78 |
| 小菇科 Mycenaceae | 2 | 12 | 5.74 | 丝盖伞属 Inocybe | 5 | 2.39 |
| 多孔菌科 Polyporaceae | 8 | 14 | 6.70 | 蜡蘑属 Laccaria | 5 | 2.39 |
| 红菇科 Russulaceae | 3 | 23 | 11.00 | 小皮伞属 Marasmius | 6 | 2.87 |
| 小菇属 Mycena | 11 | 5.26 | ||||
| 光柄菇属 Pluteus | 5 | 2.39 | ||||
| 红菇属 Russula | 17 | 8.13 | ||||
| 栓菌属 Trametes | 5 | 2.39 |
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