65 citations · 157 across the 23 of their papers we have counts for
22 papers · 1 filter
Toward Mesh-Invariant 3D Generative Deep Learning with Geometric Measures
Thomas Besnier, Sylvain Arguillère, Emery Pierson +1
3D generative modeling is accelerating as the technology allowing the capture of geometric data is developing. However, the acquired data is often inconsistent, resulting in unregi…
Bipartite Graph Diffusion Model for Human Interaction Generation
Baptiste Chopin, Hao Tang, Mohamed Daoudi
The generation of natural human motion interactions is a hot topic in computer vision and computer animation. It is a challenging task due to the diversity of possible human motion…
BaRe-ESA: A Riemannian Framework for Unregistered Human Body Shapes
Emmanuel Hartman, Emery Pierson, Martin Bauer +2
We present Basis Restricted Elastic Shape Analysis (BaRe-ESA), a novel Riemannian framework for human body scan representation, interpolation and extrapolation. BaRe-ESA operates d…
The Florence 4D Facial Expression Dataset
F. Principi, S. Berretti, C. Ferrari +3
Human facial expressions change dynamically, so their recognition / analysis should be conducted by accounting for the temporal evolution of face deformations either in 2D or 3D. W…
Automatic Estimation of Self-Reported Pain by Trajectory Analysis in the Manifold of Fixed Rank Positive Semi-Definite Matrices
Benjamin Szczapa, Mohamed Daoudi, Stefano Berretti +3
We propose an automatic method to estimate self-reported pain based on facial landmarks extracted from videos. For each video sequence, we decompose the face into four different re…
Generating Multiple 4D Expression Transitions by Learning Face Landmark Trajectories
Naima Otberdout, Claudio Ferrari, Mohamed Daoudi +2
In this work, we address the problem of 4D facial expressions generation. This is usually addressed by animating a neutral 3D face to reach an expression peak, and then get back to…
3D Shape Sequence of Human Comparison and Classification using Current and Varifolds
Emery Pierson, Mohamed Daoudi, Sylvain Arguillere
In this paper we address the task of the comparison and the classification of 3D shape sequences of human. The non-linear dynamics of the human motion and the changing of the surfa…
Interaction Transformer for Human Reaction Generation
Baptiste Chopin, Hao Tang, Naima Otberdout +2
We address the challenging task of human reaction generation, which aims to generate a corresponding reaction based on an input action. Most of the existing works do not focus on g…
3D Skeleton-based Human Motion Prediction with Manifold-Aware GAN
Baptiste Chopin, Naima Otberdout, Mohamed Daoudi +1
In this work we propose a novel solution for 3D skeleton-based human motion prediction. The objective of this task consists in forecasting future human poses based on a prior skele…
A Riemannian Framework for Analysis of Human Body Surface
Emery Pierson, Mohamed Daoudi, Alice-Barbara Tumpach
We propose a novel framework for comparing 3D human shapes under the change of shape and pose. This problem is challenging since 3D human shapes vary significantly across subjects…
Magnifying Subtle Facial Motions for Effective 4D Expression Recognition
Qingkai Zhen, Di Huang, Yunhong Wang +3
In this paper, an effective pipeline to automatic 4D Facial Expression Recognition (4D FER) is proposed. It combines two growing but disparate ideas in Computer Vision -- computing…
Human Motion Prediction Using Manifold-Aware Wasserstein GAN
Baptiste Chopin, Naima Otberdout, Mohamed Daoudi +1
Human motion prediction aims to forecast future human poses given a prior pose sequence. The discontinuity of the predicted motion and the performance deterioration in long-term ho…
Hybrid Approach for 3D Head Reconstruction: Using Neural Networks and Visual Geometry
Oussema Bouafif, Bogdan Khomutenko, Mohamed Daoudi
Recovering the 3D geometric structure of a face from a single input image is a challenging active research area in computer vision. In this paper, we present a novel method for rec…
Modelling the Statistics of Cyclic Activities by Trajectory Analysis on the Manifold of Positive-Semi-Definite Matrices
Ettore Maria Celozzi, Luca Ciabini, Luca Cultrera +4
In this paper, a model is presented to extract statistical summaries to characterize the repetition of a cyclic body action, for instance a gym exercise, for the purpose of checkin…
Automatic Estimation of Self-Reported Pain by Interpretable Representations of Motion Dynamics
Benjamin Szczapa, Mohamed Daoudi, Stefano Berretti +3
We propose an automatic method for pain intensity measurement from video. For each video, pain intensity was measured using the dynamics of facial movement using 66 facial points.…
Fitting, Comparison, and Alignment of Trajectories on Positive Semi-Definite Matrices with Application to Action Recognition
Benjamin Szczapa, Mohamed Daoudi, Stefano Berretti +3
In this paper, we tackle the problem of action recognition using body skeletons extracted from video sequences. Our approach lies in the continuity of recent works representing vid…
Dynamic Facial Expression Generation on Hilbert Hypersphere with Conditional Wasserstein Generative Adversarial Nets
Naima Otberdout, Mohamed Daoudi, Anis Kacem +2
In this work, we propose a novel approach for generating videos of the six basic facial expressions given a neutral face image. We propose to exploit the face geometry by modeling…
Automatic Analysis of Facial Expressions Based on Deep Covariance Trajectories
Naima Otberdout, Anis Kacem, Mohamed Daoudi +2
In this paper, we propose a new approach for facial expression recognition using deep covariance descriptors. The solution is based on the idea of encoding local and global Deep Co…
A Novel Geometric Framework on Gram Matrix Trajectories for Human Behavior Understanding
Anis Kacem, Mohamed Daoudi, Boulbaba Ben Amor +2
In this paper, we propose a novel space-time geometric representation of human landmark configurations and derive tools for comparison and classification. We model the temporal evo…
Deep Covariance Descriptors for Facial Expression Recognition
Naima Otberdout, Anis Kacem, Mohamed Daoudi +2
In this paper, covariance matrices are exploited to encode the deep convolutional neural networks (DCNN) features for facial expression recognition. The space geometry of the covar…
Emotion Recognition by Body Movement Representation on the Manifold of Symmetric Positive Definite Matrices
Mohamed Daoudi, Stefano Berretti, Pietro Pala +2
Emotion recognition is attracting great interest for its potential application in a multitude of real-life situations. Much of the Computer Vision research in this field has focuse…
A Novel Space-Time Representation on the Positive Semidefinite Con for Facial Expression Recognition
Anis Kacem, Mohamed Daoudi, Boulbaba Ben Amor +1
In this paper, we study the problem of facial expression recognition using a novel space-time geometric representation. We describe the temporal evolution of facial landmarks as pa…