PETRv2: A Unified Framework for 3D Perception from Multi-Camera Images
Not on the map. Why?
Cited by 25 in End-to-end autonomous driving, but placed by its own abstract, which didn’t fit.
Abstract (arXiv)
In this paper, we propose PETRv2, a unified framework for 3D perception from multi-view images. Based on PETR, PETRv2 explores the effectiveness of temporal modeling, which utilizes the temporal information of previous frames to boost 3D object detection. More specifically, we extend the 3D position embedding (3D PE) in PETR for temporal modeling. The 3D PE achieves the temporal alignment on object position of different frames. A feature-guided position encoder is further introduced to improve the data adaptability of 3D PE. To support for multi-task learning (e.g., BEV segmentation and 3D lane detection), PETRv2 provides a simple yet effective solution by introducing task-specific queries, which are initialized under different spaces. PETRv2 achieves state-of-the-art performance on 3D object detection, BEV segmentation and 3D lane detection. Detailed robustness analysis is also conducted on PETR framework. We hope PETRv2 can serve as a strong baseline for 3D perception. Code is available at urlhttps://github.com/megvii-research/PETR.
Key facts. Cited by 352 papers in the map (data through 14 Oct 2026). Builds on 48 of its 60 references that are in the map. First posted on arXiv 2 Jun 2022.
Builds on
48 of 60 references.
References · 48
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36 more
- 2020Lift, Splat, Shoot: Encoding Images From Arbitrary Camera Rigs by Implicitly Unprojecting to 3Dcited by 1,044
- 2017Focal Loss for Dense Object Detectioncited by 752
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- 2019M3D-RPN: Monocular 3D Region Proposal Network for Object Detectioncited by 252
- 2021Is Pseudo-Lidar needed for Monocular 3D Object detection?cited by 249
- 2017SSD-6D: Making RGB-based 3D detection and 6D pose estimation great againcited by 243
- 2021FIERY: Future Instance Prediction in Bird's-Eye View from Surround Monocular Camerascited by 239
- 2021Efficiently Identifying Task Groupings for Multi-Task Learningcited by 222
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- 2021Probabilistic and Geometric Depth: Detecting Objects in Perspectivecited by 191
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- 2019Cross-view Semantic Segmentation for Sensing Surroundingscited by 174
- 2021Instances as Queriescited by 158
- 2021ImVoxelNet: Image to Voxels Projection for Monocular and Multi-View General-Purpose 3D Object Detectioncited by 157
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- 2022BEVSegFormer: Bird's Eye View Semantic Segmentation From Arbitrary Camera Rigscited by 123
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- 2021CondLaneNet: a Top-to-down Lane Detection Framework Based on Conditional Convolutioncited by 95
- 2020Gen-LaneNet: A Generalized and Scalable Approach for 3D Lane Detectioncited by 75
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Citing papers per year: 2022: 31; 2023: 94; 2024: 121; 2025: 68; 2026: 38.
352 papers.
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