State-of-the-art in 360 video/image processing: Perception, assessment and compression
Nowadays, 360° video/image has been increasingly popular and drawn great attention. The
spherical viewing range of 360° video/image accounts for huge data, which pose the …
spherical viewing range of 360° video/image accounts for huge data, which pose the …
Salient object detection: A survey
Detecting and segmenting salient objects from natural scenes, often referred to as salient
object detection, has attracted great interest in computer vision. While many models have …
object detection, has attracted great interest in computer vision. While many models have …
LSNet: Lightweight spatial boosting network for detecting salient objects in RGB-thermal images
Most recent methods for RGB (red–green–blue)-thermal salient object detection (SOD)
involve several floating-point operations and have numerous parameters, resulting in slow …
involve several floating-point operations and have numerous parameters, resulting in slow …
Dynamic context-sensitive filtering network for video salient object detection
The ability to capture inter-frame dynamics has been critical to the development of video
salient object detection (VSOD). While many works have achieved great success in this field …
salient object detection (VSOD). While many works have achieved great success in this field …
Deeply supervised salient object detection with short connections
Recent progress on saliency detection is substantial, benefiting mostly from the explosive
development of Convolutional Neural Networks (CNNs). Semantic segmentation and …
development of Convolutional Neural Networks (CNNs). Semantic segmentation and …
RGB-D salient object detection via 3D convolutional neural networks
RGB-D salient object detection (SOD) recently has attracted increasing research interest
and many deep learning methods based on encoder-decoder architectures have emerged …
and many deep learning methods based on encoder-decoder architectures have emerged …
Revisiting video saliency prediction in the deep learning era
Predicting where people look in static scenes, aka visual saliency, has received significant
research interest recently. However, relatively less effort has been spent in understanding …
research interest recently. However, relatively less effort has been spent in understanding …
What do different evaluation metrics tell us about saliency models?
How best to evaluate a saliency model's ability to predict where humans look in images is an
open research question. The choice of evaluation metric depends on how saliency is …
open research question. The choice of evaluation metric depends on how saliency is …
Learning unsupervised video object segmentation through visual attention
This paper conducts a systematic study on the role of visual attention in Unsupervised Video
Object Segmentation (UVOS) tasks. By elaborately annotating three popular video …
Object Segmentation (UVOS) tasks. By elaborately annotating three popular video …
Part-object relational visual saliency
Recent years have witnessed a big leap in automatic visual saliency detection attributed to
advances in deep learning, especially Convolutional Neural Networks (CNNs). However …
advances in deep learning, especially Convolutional Neural Networks (CNNs). However …