Gaze target detection aims to predict the image location where the person is looking and the
probability that a gaze is out of the scene. Several works have tackled this task by regressing …

Gaze target detection aims to infer where each person in a scene is looking. Existing works
focus on 2D gaze and 2D saliency, but fail to exploit 3D contexts. In this work, we propose a …

Today, one of the major challenges that autonomous vehicles are facing is the ability to drive
in urban environments. Such a task requires communication between autonomous vehicles …

Although recent gaze estimation methods lay great emphasis on attentively extracting gaze-
relevant features from facial or eye images, how to define features that include gaze-relevant …

This paper addresses the gaze target detection problem in single images captured from the
third-person perspective. We present a multimodal deep architecture to infer where a person …

This paper presents a human–robot interaction method for controlling an autonomous
mobile robot with a referential pointing gesture. A human user points to a specific location …

Although gaze estimation methods have been developed with deep learning techniques,
there has been no such approach as aim to attain accurate performance in low-resolution …

Optical flow networks have been widely utilized for video saliency detection (VSD) due to
their effective performance in capturing the motion of objects. However, the use of optical …

A deep feature-based saliency model (DeepFeat) is developed to leverage understanding of
the prediction of human fixations. Conventional saliency models often predict the human …

A first set of signals corresponding to a first signal modality (such as the direction of a gaze)
during a time interval is collected from an individual. A second set of signals corresponding …