62 citations · 132 across the 16 of their papers we have counts for
18 papers
Calibration-Free 3D Multi-Camera People Tracking for Indoor Environment
Ponleur Veng, Dominique Vaufreydaz, Phutphalla Kong
Multi-Camera People Tracking (MCPT) traditionally relies on precise intrinsic and extrinsic camera calibration to project 2D detections into a unified 3D world coordinate system.Ho…
''I don't want to break it'': An Exploration of Perceived Fragility in Shape-Changing Interfaces
Eva Mackamul, Tom Maillard, Noé Marceaul +6
Shape-Changing Interfaces (SCIs) dynamically alter their form, an inherent characteristic that introduces fragility into their design. As a result, users' perceptions of an interfa…
A Comprehensive Multi-scale Approach for Speech and Dynamics Synchrony in Talking Head Generation
Louis Airale, Dominique Vaufreydaz, Xavier Alameda-Pineda
Animating still face images with deep generative models using a speech input signal is an active research topic and has seen important recent progress.However, much of the effort h…
Preliminary Study on SSCF-derived Polar Coordinate for ASR
Sotheara Leang, Eric Castelli, Dominique Vaufreydaz +1
The transition angles are defined to describe the vowel-to-vowel transitions in the acoustic space of the Spectral Subband Centroids, and the findings show that they are similar am…
Autoregressive GAN for Semantic Unconditional Head Motion Generation
Louis Airale, Xavier Alameda-Pineda, Stéphane Lathuilière +1
In this work, we address the task of unconditional head motion generation to animate still human faces in a low-dimensional semantic space from a single reference pose. Different f…
TokenCut: Segmenting Objects in Images and Videos with Self-supervised Transformer and Normalized Cut
Yangtao Wang, Xi Shen, Yuan Yuan +5
In this paper, we describe a graph-based algorithm that uses the features obtained by a self-supervised transformer to detect and segment salient objects in images and videos. With…
Self-Supervised Transformers for Unsupervised Object Discovery using Normalized Cut
Yangtao Wang, Xi Shen, Shell Hu +3
Transformers trained with self-supervised learning using self-distillation loss (DINO) have been shown to produce attention maps that highlight salient foreground objects. In this…
Navigation In Urban Environments Amongst Pedestrians Using Multi-Objective Deep Reinforcement Learning
Niranjan Deshpande, Dominique Vaufreydaz, Anne Spalanzani
Urban autonomous driving in the presence of pedestrians as vulnerable road users is still a challenging and less examined research problem. This work formulates navigation in urban…
SocialInteractionGAN: Multi-person Interaction Sequence Generation
Louis Airale, Dominique Vaufreydaz, Xavier Alameda-Pineda
Prediction of human actions in social interactions has important applications in the design of social robots or artificial avatars. In this paper, we focus on a unimodal representa…
Behavioral decision-making for urban autonomous driving in the presence of pedestrians using Deep Recurrent Q-Network
Niranjan Deshpande, Dominique Vaufreydaz, Anne Spalanzani
Decision making for autonomous driving in urban environments is challenging due to the complexity of the road structure and the uncertainty in the behavior of diverse road users. T…
Group-Level Emotion Recognition Using a Unimodal Privacy-Safe Non-Individual Approach
Anastasia Petrova, Dominique Vaufreydaz, Philippe Dessus
This article presents our unimodal privacy-safe and non-individual proposal for the audio-video group emotion recognition subtask at the Emotion Recognition in the Wild (EmotiW) Ch…
Deep learning investigation for chess player attention prediction using eye-tracking and game data
Justin Le Louedec, Thomas Guntz, James Crowley +1
This article reports on an investigation of the use of convolutional neural networks to predict the visual attention of chess players. The visual attention model described in this…
The Role of Emotion in Problem Solving: First Results from Observing Chess
Thomas Guntz, James Crowley, Dominique Vaufreydaz +2
In this paper we present results from recent experiments that suggest that chess players associate emotions to game situations and reactively use these associations to guide search…
Building Prior Knowledge: A Markov Based Pedestrian Prediction Model Using Urban Environmental Data
Pavan Vasishta, Dominique Vaufreydaz, Anne Spalanzani
Autonomous Vehicles navigating in urban areas have a need to understand and predict future pedestrian behavior for safer navigation. This high level of situational awareness requir…
Smartphone-based user positioning in a multiple-user context with Wi-Fi and Bluetooth
Viet-Cuong Ta, Trung-Kien Dao, Dominique Vaufreydaz +1
In a multiuser context, the Bluetooth data from the smartphone could give an approximation of the distance between users. Meanwhile, the Wi-Fi data can be used to calculate the use…
Personal space of autonomous car's passengers sitting in the driver's seat
Eleonore Ferrier-Barbut, Dominique Vaufreydaz, Jean-Alix David +2
This article deals with the specific context of an autonomous car navigating in an urban center within a shared space between pedestrians and cars. The driver delegates the control…
Multimodal Observation and Interpretation of Subjects Engaged in Problem Solving
Thomas Guntz, Raffaella Balzarini, Dominique Vaufreydaz +1
In this paper we present the first results of a pilot experiment in the capture and interpretation of multimodal signals of human experts engaged in solving challenging chess probl…
Starting engagement detection towards a companion robot using multimodal features
Dominique Vaufreydaz, Wafa Johal, Claudine Combe
Recognition of intentions is a subconscious cognitive process vital to human communication. This skill enables anticipation and increases the quality of interactions between humans…