# RAPiD: Rotation-Aware People Detection in Overhead Fisheye Images

arXiv: https://arxiv.org/abs/2005.11623 · HTML: https://mlsanity.com/paper/2005.11623/

## Key facts

- Cited by 17 papers in the map (data through 14 Oct 2026).
- First posted on arXiv 23 May 2020.

## Built on by (most cited first, 17 of 17)

- [Large-Scale Person Detection and Localization using Overhead Fisheye Cameras](https://mlsanity.com/paper/2307.08252/) (2023)
- [Semi-Supervised 2D Human Pose Estimation Driven by Position Inconsistency Pseudo Label Correction Module](https://mlsanity.com/paper/2303.04346/) (2023)
- [FisheyeSuperPoint: Keypoint Detection and Description Network for Fisheye Images](https://mlsanity.com/paper/2103.00191/) (2021)
- [FRIDA: Fisheye Re-Identification Dataset with Annotations](https://mlsanity.com/paper/2210.01582/) (2022)
- [Applications of Deep Learning for Top-View Omnidirectional Imaging: A Survey](https://mlsanity.com/paper/2304.08193/) (2023)
- [ARPD: Anchor-free Rotation-aware People Detection using Topview Fisheye Camera](https://mlsanity.com/paper/2201.10107/) (2022)
- [NToP: NeRF-Powered Large-scale Dataset Generation for 2D and 3D Human Pose Estimation in Top-View Fisheye Images](https://mlsanity.com/paper/2402.18196/) (2024)
- [Estimating Distances Between People using a Single Overhead Fisheye Camera with Application to Social-Distancing Oversight](https://mlsanity.com/paper/2303.11520/) (2023)
- [Streaming Object Detection on Fisheye Cameras for Automatic Parking](https://mlsanity.com/paper/2305.14713/) (2023)
- [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)
- [Segmentation-Based Bounding Box Generation for Omnidirectional Pedestrian Detection](https://mlsanity.com/paper/2104.13764/) (2021)
- [Spatio-Visual Fusion-Based Person Re-Identification for Overhead Fisheye Images](https://mlsanity.com/paper/2212.11477/) (2022)
- [CRRS: Concentric Rectangles Regression Strategy for Multi-point Representation on Fisheye Images](https://mlsanity.com/paper/2303.14639/) (2023)
- [Panoramic Distortion-Aware Tokenization for Person Detection and Localization in Overhead Fisheye Images](https://mlsanity.com/paper/2503.14228/) (2025)
- [GTATrack: Winner Solution to SoccerTrack 2025 with Deep-EIoU and Global Tracklet Association](https://mlsanity.com/paper/2602.00484/) (2026)
- [PMOF: A Dataset and Benchmark for Passenger Monitoring Using Overhead Fisheye Cameras](https://mlsanity.com/paper/2606.13910/) (2026)

## Abstract (arXiv)

Recent methods for people detection in overhead, fisheye images either use radially-aligned bounding boxes to represent people, assuming people always appear along image radius or require significant pre-/post-processing which radically increases computational complexity. In this work, we develop an end-to-end rotation-aware people detection method, named RAPiD, that detects people using arbitrarily-oriented bounding boxes. Our fully-convolutional neural network directly regresses the angle of each bounding box using a periodic loss function, which accounts for angle periodicities. We have also created a new dataset with spatio-temporal annotations of rotated bounding boxes, for people detection as well as other vision tasks in overhead fisheye videos. We show that our simple, yet effective method outperforms state-of-the-art results on three fisheye-image datasets. Code and dataset are available at http://vip.bu.edu/rapid .