204 citations · 426 across the 23 of their papers we have counts for
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Efficient Convolutional Neural Networks for Depth-Based Multi-Person Pose Estimation
Angel Martínez-González, Michael Villamizar, Olivier Canévet +1
Achieving robust multi-person 2D body landmark localization and pose estimation is essential for human behavior and interaction understanding as encountered for instance in HRI set…
Unsupervised Representation Learning for Gaze Estimation
Yu Yu, Jean-Marc Odobez
Although automatic gaze estimation is very important to a large variety of application areas, it is difficult to train accurate and robust gaze models, in great part due to the dif…
Real-time Convolutional Networks for Depth-based Human Pose Estimation
Angel Martínez-González, Michael Villamizar, Olivier Canévet +1
We propose to combine recent Convolutional Neural Networks (CNN) models with depth imaging to obtain a reliable and fast multi-person pose estimation algorithm applicable to Human…
MuMMER: Socially Intelligent Human-Robot Interaction in Public Spaces
Mary Ellen Foster, Bart Craenen, Amol Deshmukh +27
In the EU-funded MuMMER project, we have developed a social robot designed to interact naturally and flexibly with users in public spaces such as a shopping mall. We present the la…
Improving Few-Shot User-Specific Gaze Adaptation via Gaze Redirection Synthesis
Yu Yu, Gang Liu, Jean-Marc Odobez
As an indicator of human attention gaze is a subtle behavioral cue which can be exploited in many applications. However, inferring 3D gaze direction is challenging even for deep ne…
A Differential Approach for Gaze Estimation
Gang Liu, Yu Yu, Kenneth A. Funes Mora +1
Non-invasive gaze estimation methods usually regress gaze directions directly from a single face or eye image. However, due to important variabilities in eye shapes and inner eye s…
Theoretical Guarantees of Deep Embedding Losses Under Label Noise
Nam Le, Jean-Marc Odobez
Collecting labeled data to train deep neural networks is costly and even impractical for many tasks. Thus, research effort has been focused in automatically curated datasets or uns…