FB-BEV: BEV Representation from Forward-Backward View Transformations
Zhiqi Li, Zhiding Yu, Wenhai Wang, Anima Anandkumar, Tong Lu, José M. Álvarez
Abstract
View Transformation Module (VTM), where transformations happen between multi-view image features and Bird-Eye-View (BEV) representation, is a crucial step in camera-based BEV perception systems. Currently, the two most prominent VTM paradigms are forward projection and backward projection. Forward projection, represented by Lift-Splat-Shoot, leads to sparsely projected BEV features without post-processing. Backward projection, with BEV-Former being an example, tends to generate false-positive BEV features from incorrect projections due to the lack of utilization on depth. To address the above limitations, we propose a novel forward-backward view transformation module. Our approach compensates for the deficiencies in both existing methods, allowing them to enhance each other to obtain higher quality BEV representations mutually. We instantiate the proposed module with FB-BEV, which achieves a new state-of-the-art result of 62.4% NDS on the nuScenes test set. Code and models are available at https://github.com/NVlabs/FB-BEV.
Ask about this paper
Your agent reads all of it.
Lune indexed this paper to the last equation, along with the top-tier papers that cite it. Ask a question and the answer quotes them.
Your agent calls
Luneget_paper_fulltext
Free to start. No credit card required.
Terminal
Install the CLIlune papers fulltext 1b176b3c-4fd9-4ee2-8726-0af29b1de6fcCited by top-tier papers41
- Memory-and-Anticipation Transformer for Online Action UnderstandingJiahao Wang, Guo Chen, Yifei Huang, Limin Wang et al.ICCV 2023 · 72 citations
- OctreeOcc: Efficient and Multi-Granularity Occupancy Prediction Using Octree QueriesYuhang Lu, Xinge Zhu, Tai Wang, Yuexin MaNeurIPS 2024 · 70 citations
- COTR: Compact Occupancy TRansformer for Vision-Based 3D Occupancy PredictionQihang Ma, Xin Tan, Yanyun Qu, Lizhuang Ma et al.CVPR 2024 · 30 citations
- GeoBEV: Learning Geometric BEV Representation for Multi-view 3D Object DetectionJinqing Zhang, Yanan Zhang, Yunlong Qi, Zehua Fu et al.AAAI 2025 · 22 citations
- Regulating Intermediate 3D Features for Vision-Centric Autonomous DrivingJunkai Xu, Liang Peng, Haoran Cheng, Linxuan Xia et al.AAAI 2024 · 14 citations
Builds on16
- Swin Transformer: Hierarchical Vision Transformer using Shifted WindowsZe Liu, Yutong Lin, Yue Cao, Han Hu et al.ICCV 2021 · 31,683 citations
- Deformable DETR: Deformable Transformers for End-to-End Object DetectionXizhou Zhu, Weijie Su, Lewei Lu, Bin Li et al.ICLR 2021 · 7,353 citations
- A ConvNet for the 2020sZhuang Liu, Hanzi Mao, Chao-Yuan Wu, Christoph Feichtenhofer et al.CVPR 2022 · 6,782 citations
- BEVDepth: Acquisition of Reliable Depth for Multi-View 3D Object DetectionYinhao Li, Zheng Ge, Guanyi Yu, Jinrong Yang et al.AAAI 2023 · 954 citations
- TransFusion: Robust LiDAR-Camera Fusion for 3D Object Detection with TransformersXuyang Bai, Zeyu Hu, Xinge Zhu, Qingqiu Huang et al.CVPR 2022 · 794 citations
Related papers
- MatrixVT: Efficient Multi-Camera to BEV Transformation for 3D PerceptionHongyu Zhou, Zheng Ge, Zeming Li, Xiangyu ZhangICCV 2023 · 62 citations
- EVT: Efficient View Transformation for Multi-Modal 3D Object DetectionYongjin Lee, Hyeon Mun Jeong, Yurim Jeon, Sanghyun KimICCV 2025 · 5 citations
- RayFormer: Improving Query-Based Multi-Camera 3D Object Detection via Ray-Centric StrategiesXiaomeng Chu, Jiajun Deng, Guoliang You, Yifan Duan et al.ACM MM 2024 · 7 citations
- CycleBEV: Regularizing View Transformation Networks via View Cycle Consistency for Bird’s-Eye-View Semantic SegmentationJeongbin Hong, Dooseop Choi, Taeg-Hyun An, KYOUNG AN AN et al.CVPR 2026 · 1 citation
- BAEFormer: Bi-Directional and Early Interaction Transformers for Bird's Eye View Semantic SegmentationCong Pan, Yonghao He, Junran Peng, Qian Zhang et al.CVPR 2023
