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 …
Predicting human eye fixations via an lstm-based saliency attentive model
Data-driven saliency has recently gained a lot of attention thanks to the use of convolutional
neural networks for predicting gaze fixations. In this paper, we go beyond standard …
neural networks for predicting gaze fixations. In this paper, we go beyond standard …
Saliency in VR: How do people explore virtual environments?
Understanding how people explore immersive virtual environments is crucial for many
applications, such as designing virtual reality (VR) content, developing new compression …
applications, such as designing virtual reality (VR) content, developing new compression …
Salgan: Visual saliency prediction with generative adversarial networks
We introduce SalGAN, a deep convolutional neural network for visual saliency prediction
trained with adversarial examples. The first stage of the network consists of a generator …
trained with adversarial examples. The first stage of the network consists of a generator …
Salicon: Reducing the semantic gap in saliency prediction by adapting deep neural networks
Saliency in Context (SALICON) is an ongoing effort that aims at understanding and
predicting visual attention. Conventional saliency models typically rely on low-level image …
predicting visual attention. Conventional saliency models typically rely on low-level image …
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 …
Shallow and deep convolutional networks for saliency prediction
The prediction of salient areas in images has been traditionally addressed with hand-crafted
features based on neuroscience principles. This paper, however, addresses the problem …
features based on neuroscience principles. This paper, however, addresses the problem …
Deepfix: A fully convolutional neural network for predicting human eye fixations
SSS Kruthiventi, K Ayush… - IEEE Transactions on …, 2017 - ieeexplore.ieee.org
Understanding and predicting the human visual attention mechanism is an active area of
research in the fields of neuroscience and computer vision. In this paper, we propose …
research in the fields of neuroscience and computer vision. In this paper, we propose …
Understanding low-and high-level contributions to fixation prediction
Understanding where people look in images is an important problem in computer vision.
Despite significant research, it remains unclear to what extent human fixations can be …
Despite significant research, it remains unclear to what extent human fixations can be …