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PETR: Position Embedding Transformation for Multi-View 3D Object Detection

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arxiv 2203.05625 v3 pith:2FEFMHF4 submitted 2022-03-10 cs.CV

PETR: Position Embedding Transformation for Multi-View 3D Object Detection

Yingfei Liu , Tiancai Wang , Xiangyu Zhang , Jian Sun This is my paper
classification cs.CV
keywords petrobjectdetectionfeaturespositionembeddingmulti-viewposition-aware
verification ladder T0 review T1 audit T2 compute T3 formal T4 reserved
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In this paper, we develop position embedding transformation (PETR) for multi-view 3D object detection. PETR encodes the position information of 3D coordinates into image features, producing the 3D position-aware features. Object query can perceive the 3D position-aware features and perform end-to-end object detection. PETR achieves state-of-the-art performance (50.4% NDS and 44.1% mAP) on standard nuScenes dataset and ranks 1st place on the benchmark. It can serve as a simple yet strong baseline for future research. Code is available at \url{https://github.com/megvii-research/PETR}.

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Cited by 7 Pith papers

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