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# BEVFusion
[![PWC](https://img.shields.io/endpoint.svg?url=https://paperswithcode.com/badge/bevfusion-multi-task-multi-sensor-fusion-with/3d-object-detection-on-nuscenes)](https://paperswithcode.com/sota/3d-object-detection-on-nuscenes?p=bevfusion-multi-task-multi-sensor-fusion-with)
### [website](http://bevfusion.mit.edu/) | [paper](https://arxiv.org/abs/2205.13542) | [video](https://www.youtube.com/watch?v=uCAka90si9E)
![demo](assets/demo.gif)
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BEVFusion is based on [mmdetection3d](https://github.com/open-mmlab/mmdetection3d). It is also greatly inspired by the following outstanding contributions to the open-source community: [LSS](https://github.com/nv-tlabs/lift-splat-shoot), [BEVDet](https://github.com/HuangJunjie2017/BEVDet), [TransFusion](https://github.com/XuyangBai/TransFusion), [CenterPoint](https://github.com/tianweiy/CenterPoint), [MVP](https://github.com/tianweiy/MVP), [FUTR3D](https://arxiv.org/abs/2203.10642), [CVT](https://github.com/bradyz/cross_view_transformers) and [DETR3D](https://github.com/WangYueFt/detr3d).
Please also check out related papers in the camera-only 3D perception community such as [BEVDet4D](https://arxiv.org/abs/2203.17054), [BEVerse](https://arxiv.org/abs/2205.09743), [BEVFormer](https://arxiv.org/abs/2203.17270), [M2BEV](https://arxiv.org/abs/2204.05088) and [PETR](https://arxiv.org/abs/2203.05625), which might be interesting future extensions to BEVFusion.
Please also check out related papers in the camera-only 3D perception community such as [BEVDet4D](https://arxiv.org/abs/2203.17054), [BEVerse](https://arxiv.org/abs/2205.09743), [BEVFormer](https://arxiv.org/abs/2203.17270), [M2BEV](https://arxiv.org/abs/2204.05088), [PETR](https://arxiv.org/abs/2203.05625) and [PETRv2](https://arxiv.org/abs/2206.01256), which might be interesting future extensions to BEVFusion.
## Citation