Exploring Surround-View Fisheye Camera 3D Object Detection
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arXiv
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| Main Authors: | , , , , , , |
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| Format: | Preprint |
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2025
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| _version_ | 1866915634808356864 |
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| author | Li, Changcai Lin, Wenwei Hou, Zuoxun Chen, Gang Zhang, Wei Zhou, Huihui Zheng, Weishi |
| author_facet | Li, Changcai Lin, Wenwei Hou, Zuoxun Chen, Gang Zhang, Wei Zhou, Huihui Zheng, Weishi |
| contents | In this work, we explore the technical feasibility of implementing end-to-end 3D object detection (3DOD) with surround-view fisheye camera system. Specifically, we first investigate the performance drop incurred when transferring classic pinhole-based 3D object detectors to fisheye imagery. To mitigate this, we then develop two methods that incorporate the unique geometry of fisheye images into mainstream detection frameworks: one based on the bird's-eye-view (BEV) paradigm, named FisheyeBEVDet, and the other on the query-based paradigm, named FisheyePETR. Both methods adopt spherical spatial representations to effectively capture fisheye geometry. In light of the lack of dedicated evaluation benchmarks, we release Fisheye3DOD, a new open dataset synthesized using CARLA and featuring both standard pinhole and fisheye camera arrays. Experiments on Fisheye3DOD show that our fisheye-compatible modeling improves accuracy by up to 6.2% over baseline methods. |
| format | Preprint |
| id |
arxiv_https___arxiv_org_abs_2511_18695 |
| institution | arXiv |
| publishDate | 2025 |
| record_format | arxiv |
| spellingShingle | Exploring Surround-View Fisheye Camera 3D Object Detection Li, Changcai Lin, Wenwei Hou, Zuoxun Chen, Gang Zhang, Wei Zhou, Huihui Zheng, Weishi Computer Vision and Pattern Recognition I.2.10; I.4.8 In this work, we explore the technical feasibility of implementing end-to-end 3D object detection (3DOD) with surround-view fisheye camera system. Specifically, we first investigate the performance drop incurred when transferring classic pinhole-based 3D object detectors to fisheye imagery. To mitigate this, we then develop two methods that incorporate the unique geometry of fisheye images into mainstream detection frameworks: one based on the bird's-eye-view (BEV) paradigm, named FisheyeBEVDet, and the other on the query-based paradigm, named FisheyePETR. Both methods adopt spherical spatial representations to effectively capture fisheye geometry. In light of the lack of dedicated evaluation benchmarks, we release Fisheye3DOD, a new open dataset synthesized using CARLA and featuring both standard pinhole and fisheye camera arrays. Experiments on Fisheye3DOD show that our fisheye-compatible modeling improves accuracy by up to 6.2% over baseline methods. |
| title | Exploring Surround-View Fisheye Camera 3D Object Detection |
| topic | Computer Vision and Pattern Recognition I.2.10; I.4.8 |
| url | https://arxiv.org/abs/2511.18695 |