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• W3204679535 abstract "Exploring to what humans pay attention in dynamic panoramic scenes is useful for many fundamental applications, including augmented reality (AR) in retail, AR-powered recruitment, and visual language navigation. With this goal in mind, we propose PV-SOD, a new task that aims to segment salient objects from panoramic videos. In contrast to existing fixation-/object-level saliency detection tasks, we focus on audio-induced salient object detection (SOD), where the salient objects are labeled with the guidance of audio-induced eye movements. To support this task, we collect the first large-scale dataset, named ASOD60K, which contains 4K-resolution video frames annotated with a six-level hierarchy, thus distinguishing itself with richness, diversity and quality. Specifically, each sequence is marked with both its super-/sub-class, with objects of each sub-class being further annotated with human eye fixations, bounding boxes, object-/instance-level masks, and associated attributes (e.g., geometrical distortion). These coarse-to-fine annotations enable detailed analysis for PV-SOD modelling, e.g., determining the major challenges for existing SOD models, and predicting scanpaths to study the long-term eye fixation behaviors of humans. We systematically benchmark 11 representative approaches on ASOD60K and derive several interesting findings. We hope this study could serve as a good starting point for advancing SOD research towards panoramic videos. The dataset and benchmark will be made publicly available at https://github.com/PanoAsh/ASOD60K." @default.
• W3204679535 created "2021-10-11" @default.
• W3204679535 creator A5001285878 @default.
• W3204679535 creator A5025883253 @default.
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• W3204679535 creator A5044757881 @default.
• W3204679535 creator A5056294284 @default.
• W3204679535 creator A5082634513 @default.
• W3204679535 date "2021-07-24" @default.
• W3204679535 modified "2023-09-27" @default.
• W3204679535 title "ASOD60K: An Audio-Induced Salient Object Detection Dataset for Panoramic Videos" @default.
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• W3204679535 doi "https://doi.org/10.48550/arxiv.2107.11629" @default.
• W3204679535 hasPublicationYear "2021" @default.
• W3204679535 type Work @default.

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