# 3D Object Detection from a Single Fisheye Image Without a Single Fisheye Training Image

arXiv: https://arxiv.org/abs/2003.03759 · HTML: https://mlsanity.com/paper/2003.03759/

## Key facts

- Cited by 13 papers in the map (data through 14 Oct 2026).
- First posted on arXiv 8 Mar 2020.

## Built on by (most cited first, 13 of 13)

- [Surround-view Fisheye Camera Perception for Automated Driving: Overview, Survey and Challenges](https://mlsanity.com/paper/2205.13281/) (2022)
- [Near-field Perception for Low-Speed Vehicle Automation using Surround-view Fisheye Cameras](https://mlsanity.com/paper/2103.17001/) (2021)
- [SimFIR: A Simple Framework for Fisheye Image Rectification with Self-supervised Representation Learning](https://mlsanity.com/paper/2308.09040/) (2023)
- [DarSwin: Distortion Aware Radial Swin Transformer](https://mlsanity.com/paper/2304.09691/) (2023)
- [Exploiting the Distortion-Semantic Interaction in Fisheye Data](https://mlsanity.com/paper/2305.00079/) (2023)
- [Dur360BEV: A Real-world 360-degree Single Camera Dataset and Benchmark for Bird-Eye View Mapping in Autonomous Driving](https://mlsanity.com/paper/2503.00675/) (2025)
- [SoK: Vehicle Orientation Representations for Deep Rotation Estimation](https://mlsanity.com/paper/2112.04421/) (2021)
- [DarSwin-Unet: Distortion Aware Encoder-Decoder Architecture](https://mlsanity.com/paper/2407.17328/) (2024)
- [QueryCDR: Query-Based Controllable Distortion Rectification Network for Fisheye Images](https://mlsanity.com/paper/2412.13496/) (2024)
- [Systematic Comparison of Projection Methods for Monocular 3D Human Pose Estimation on Fisheye Images](https://mlsanity.com/paper/2506.19747/) (2025)
- [Exploring Surround-View Fisheye Camera 3D Object Detection](https://mlsanity.com/paper/2511.18695/) (2025)
- [MCPDepth: Omnidirectional Depth Estimation via Stereo Matching from Multi-Cylindrical Panoramas](https://mlsanity.com/paper/2408.01653/) (2024)
- [Towards Accurate Single Panoramic 3D Detection: A Semantic Gaussian Centric Approach](https://mlsanity.com/paper/2605.14601/) (2026)

## Abstract (arXiv)

Existing monocular 3D object detection methods have been demonstrated on rectilinear perspective images and fail in images with alternative projections such as those acquired by fisheye cameras. Previous works on object detection in fisheye images have focused on 2D object detection, partly due to the lack of 3D datasets of such images. In this work, we show how to use existing monocular 3D object detection models, trained only on rectilinear images, to detect 3D objects in images from fisheye cameras, without using any fisheye training data. We outperform the only existing method for monocular 3D object detection in panoramas on a benchmark of synthetic data, despite the fact that the existing method trains on the target non-rectilinear projection whereas we train only on rectilinear images. We also experiment with an internal dataset of real fisheye images.