FDDB-360: Face Detection in 360-degree Fisheye Images
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Abstract (arXiv)
360-degree cameras offer the possibility to cover a large area, for example an entire room, without using multiple distributed vision sensors. However, geometric distortions introduced by their lenses make computer vision problems more challenging. In this paper we address face detection in 360-degree fisheye images. We show how a face detector trained on regular images can be re-trained for this purpose, and we also provide a 360-degree fisheye-like version of the popular FDDB face detection dataset, which we call FDDB-360.
Key facts. Cited by 4 papers in the map (data through 7 Oct 2026). First posted on arXiv 7 Feb 2019.
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Citing papers per year: 2022: 2; 2023: 1; 2024: 1.
4 papers.
- 2022Deep Learning for Omnidirectional Vision: A Survey and New Perspectivescited by 38
- 2022Privacy-preserving Online AutoML for Domain-Specific Face Detectioncited by 4
- 2023Sector Patch Embedding: An Embedding Module Conforming to The Distortion Pattern of Fisheye Imagecited by 2
- 2024Location-guided Head Pose Estimation for Fisheye Imagecited by 0
- 2024Location-guided Head Pose Estimation for Fisheye Image28 Feb 2024
- 2023Sector Patch Embedding: An Embedding Module Conforming to The Distortion Pattern of Fisheye Image26 Mar 2023
- 2022Deep Learning for Omnidirectional Vision: A Survey and New Perspectives21 May 2022
- 2022Privacy-preserving Online AutoML for Domain-Specific Face Detection16 Mar 2022