In this work, we propose a deep audio-visual fusion model to estimate the saliency of videos.
The model extracts visual and audio features with two separate branches and fuses them to …

Current top-performing saliency prediction methods of omnidirectional images (ODIs)
depend on deep feedforward convolutional neural networks (CNNs), benefiting from their …

Saliency detection by human refers to the ability to identify pertinent information using our
perceptive and cognitive capabilities. While human perception is attracted by visual stimuli …

Salient object detection represents a novel preprocessing stage of many practical image
applications in the discipline of computer vision. Saliency detection is generally a complex …

Many modern computer vision systems include several modules that perform different
processing operations packaged as a single pipeline architecture. This generally introduces …

Salient object detection is a challenging task in the computer vision due to complexity of
images and insufficiency of a single feature for saliency map generation. The performance of …

In recent years, saliency detection is playing vital role in many computer vision tasks. Due to
the diversity of visual pattern in natural images, a specific saliency approach is hardly …

Despite the wide success in many vision tasks, it is still challenging for Convolutional Neural
Networks (CNNs) to perform saliency detection due to their limited receptive fields and lack …

In order to accurately detect the abnormal looseness of strapping in the process of steel coil
hoisting, an accurate detection method of strapping abnormality based on CCD structured …

Visual saliency models are widely used for salient region detection in natural images.
However, limited work has been carried out for detecting diagnostically important region in …