SHD360: A Benchmark Dataset for Salient Human Detection in 360° Videos
Yi Zhang, Lu Zhang, Kang Wang, Wassim Hamidouche, Olivier Deforges
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- github.com/PanoAsh/SHD360OfficialIn paperpytorch★ 6
Abstract
Salient human detection (SHD) in dynamic 360 immersive videos is of great importance for various applications such as robotics, inter-human and human-object interaction in augmented reality. However, 360 video SHD has been seldom discussed in the computer vision community due to a lack of datasets with large-scale omnidirectional videos and rich annotations. To this end, we propose SHD360, the first 360 video SHD dataset which contains various real-life daily scenes. Since so far there is no method proposed for 360 image/video SHD, we systematically benchmark 11 representative state-of-the-art salient object detection (SOD) approaches on our SHD360, and explore key issues derived from extensive experimenting results. We hope our proposed dataset and benchmark could serve as a good starting point for advancing human-centric researches towards 360 panoramic data.