Recognizing Human Visual Focus of Attention from Head Pose in Meetings

Chat with Graph Search

Ask any question about EPFL courses, lectures, exercises, research, news, etc. or try the example questions below.

DISCLAIMER: The Graph Chatbot is not programmed to provide explicit or categorical answers to your questions. Rather, it transforms your questions into API requests that are distributed across the various IT services officially administered by EPFL. Its purpose is solely to collect and recommend relevant references to content that you can explore to help you answer your questions.

Vision is an extraordinary sense through which we can appreciate the beauty of the world we live in, gain invaluable knowledge and communicate with others using visual expression and arts. On the contrary, blindness is a threatening medical condition disru ...

The ability to predict the spatial distribution of tree root system variables (e.g., the Root system Area (RA), the maximum root diameter, the number of roots in diameter classes, the density of fine roots, etc.) under different environmental conditions is ...

In this study, we present the deep learning image segmentation model for drone-based grain size analysis of gravel bars called GALET. The objectives are to quantify the performance of the code and to test its applicability in river research and management. ...

During the Artificial Intelligence (AI) revolution of the past decades, deep neural networks have been widely used and have achieved tremendous success in visual recognition. Unfortunately, deploying deep models is challenging because of their huge model s ...

Food consumption is among the activities with the most significant environmental impacts, and furthermore contributes to rising health costs. We explored the factors that foster or hinder healthy and sustainable eating in Switzerland. Based on an online ho ...

More and more intelligent systems have to interact with humans. In order to communicate efficiently, these systems need to perceive and understand us. A key factor of communication is the people's visual focus of attention (VFOA), which is useful to estima ...

Remote sensing visual question answering (RSVQA) opens new avenues to promote the use of satellites data, by interfacing satellite image analysis with natural language processing. Capitalizing on the remarkable advances in natural language processing and c ...

State-of-the-art training algorithms for deep learning models are based on stochastic gradient descent (SGD). Recently, many variations have been explored: perturbing parameters for better accuracy (such as in Extra-gradient), limiting SGD updates to a sub ...

Human vision has evolved to make sense of a world in which elements almost never appear in isolation. Surprisingly, the recognition of an element in a visual scene is strongly limited by the presence of other nearby elements, a phenomenon known as visual c ...

Existing research on user’s satisfaction at the workplace have shown that occupants’ perceived comfort depends on a number of environmental and non-environmental factors and that forgiveness, meant as the indulgent attitude towards inadequate indoor enviro ...

Recognizing Human Visual Focus of Attention from Head Pose in Meetings

Chat with Graph Search

Advances in visual prostheses: engineering and biological challenges

Tree root distribution modelling in different environmental conditions

GALET: A deep learning image segmentation model for drone-based grain size analysis of gravel bars

Improving the Training of Compact Neural Networks for Visual Recognition

Drivers and Barriers Toward Healthy and Environmentally Sustainable Eating in Switzerland: Linking Impacts to Intentions and Practices

Modeling and Inferring Attention between Humans or for Human-Robot Interactions

Language Transformers for Remote Sensing Visual Question Answering

Masked Training of Neural Networks with Partial Gradients

Crowding and the importance of grouping and segmentation processes in human vision

The influence of façade and space design on building occupants’ indoor experience