The multimodal task of Visual Question Answering (VQA) encompassing elements of
Computer Vision (CV) and Natural Language Processing (NLP), aims to generate answers …

While 360 cameras offer tremendous new possibilities in vision, graphics, and augmented
reality, the spherical images they produce make core feature extraction non-trivial …

We introduce SaltiNet, a deep neural network for scanpath prediction trained on 360-degree
images. The model is based on a temporal-aware novel representation of saliency …

Viewport prediction for 360 video forecasts a viewer's viewport when he/she watches a 360
video with a head-mounted display, which benefits many VR/AR applications such as 360 …

Audio-visual saliency prediction can draw support from diverse modality complements but
further performance enhancement is still challenged by customized architectures as well as …

Narrated 360 videos are typically provided in many touring scenarios to mimic real-world
experience. However, previous work has shown that smart assistance (ie, providing visual …

In this paper, we propose a method of extracting feature descriptors from discrete spherical
images using convolutional neural networks (CNNs). First, a captured full-view image is …

We introduce deep neural networks for scanpath and saliency prediction trained on 360-
degree images. The scanpath prediction model called SaltiNet is based on a temporal …

In this work, we present an integrated system for spatio-temporal summarization of 360-
degrees videos. The video summary production involves the detection of salient events in …

360° videos have been widely used with the development of virtual reality technology and
triggered a demand to determine the most visually attractive objects in them, aka 360° video …