23 citations · 51 across the 20 of their papers we have counts for
21 papers
When AUC Misleads: Polarization-Aware Evaluation of Deepfake Detectors under Domain Shift
Dat Nguyen, Cosmin Radoi, Romain Hermary +4
Recent advances in generative AI, such as diffusion models and face-swapping tools, have enabled the creation of highly realistic deepfakes, leading to real-world harms including f…
LAA-X: Unified Localized Artifact Attention for Quality-Agnostic and Generalizable Face Forgery Detection
Dat Nguyen, Enjie Ghorbel, Anis Kacem +2
In this paper, we propose Localized Artifact Attention X (LAA-X), a novel deepfake detection framework that is both robust to high-quality forgeries and capable of generalizing to…
Cov2Pose: Leveraging Spatial Covariance for Direct Manifold-aware 6-DoF Object Pose Estimation
Nassim Ali Ousalah, Peyman Rostami, Vincent Gaudillière +4
In this paper, we address the problem of 6-DoF object pose estimation from a single RGB image. Indirect methods that typically predict intermediate 2D keypoints, followed by a Pers…
FPG-NAS: FLOPs-Aware Gated Differentiable Neural Architecture Search for Efficient 6DoF Pose Estimation
Nassim Ali Ousalah, Peyman Rostami, Anis Kacem +3
We introduce FPG-NAS, a FLOPs-aware Gated Differentiable Neural Architecture Search framework for efficient 6DoF object pose estimation. Estimating 3D rotation and translation from…
Domain Adaptation for Multi-label Image Classification: a Discriminator-free Approach
Inder Pal Singh, Enjie Ghorbel, Anis Kacem +1
This paper introduces a discriminator-free adversarial-based approach termed DDA-MLIC for Unsupervised Domain Adaptation (UDA) in the context of Multi-Label Image Classification (M…
Uncertainty-Aware Knowledge Distillation for Compact and Efficient 6DoF Pose Estimation
Nassim Ali Ousalah, Anis Kacem, Enjie Ghorbel +2
Compact and efficient 6DoF object pose estimation is crucial in applications such as robotics, augmented reality, and space autonomous navigation systems, where lightweight models…
When Unsupervised Domain Adaptation meets One-class Anomaly Detection: Addressing the Two-fold Unsupervised Curse by Leveraging Anomaly Scarcity
Nesryne Mejri, Enjie Ghorbel, Anis Kacem +3
This paper introduces the first fully unsupervised domain adaptation (UDA) framework for unsupervised anomaly detection (UAD). The performance of UAD techniques degrades significan…
Audio-Visual Deepfake Detection With Local Temporal Inconsistencies
Marcella Astrid, Enjie Ghorbel, Djamila Aouada
This paper proposes an audio-visual deepfake detection approach that aims to capture fine-grained temporal inconsistencies between audio and visual modalities. To achieve this, bot…
Vulnerability-Aware Spatio-Temporal Learning for Generalizable Deepfake Video Detection
Dat Nguyen, Marcella Astrid, Anis Kacem +2
Detecting deepfake videos is highly challenging given the complexity of characterizing spatio-temporal artifacts. Most existing methods rely on binary classifiers trained using rea…
FakeFormer: Efficient Vulnerability-Driven Transformers for Generalisable Deepfake Detection
Dat Nguyen, Marcella Astrid, Enjie Ghorbel +1
Recently, Vision Transformers (ViTs) have achieved unprecedented effectiveness in the general domain of image classification. Nonetheless, these models remain underexplored in the…
A Hitchhikers Guide to Fine-Grained Face Forgery Detection Using Common Sense Reasoning
Niki Maria Foteinopoulou, Enjie Ghorbel, Djamila Aouada
Explainability in artificial intelligence is crucial for restoring trust, particularly in areas like face forgery detection, where viewers often struggle to distinguish between rea…
Detecting Audio-Visual Deepfakes with Fine-Grained Inconsistencies
Marcella Astrid, Enjie Ghorbel, Djamila Aouada
Existing methods on audio-visual deepfake detection mainly focus on high-level features for modeling inconsistencies between audio and visual data. As a result, these approaches us…
Statistics-aware Audio-visual Deepfake Detector
Marcella Astrid, Enjie Ghorbel, Djamila Aouada
In this paper, we propose an enhanced audio-visual deep detection method. Recent methods in audio-visual deepfake detection mostly assess the synchronization between audio and visu…
Targeted Augmented Data for Audio Deepfake Detection
Marcella Astrid, Enjie Ghorbel, Djamila Aouada
The availability of highly convincing audio deepfake generators highlights the need for designing robust audio deepfake detectors. Existing works often rely solely on real and fake…
LAA-Net: Localized Artifact Attention Network for Quality-Agnostic and Generalizable Deepfake Detection
Dat Nguyen, Nesryne Mejri, Inder Pal Singh +5
This paper introduces a novel approach for high-quality deepfake detection called Localized Artifact Attention Network (LAA-Net). Existing methods for high-quality deepfake detecti…
DermSynth3D: Synthesis of in-the-wild Annotated Dermatology Images
Ashish Sinha, Jeremy Kawahara, Arezou Pakzad +6
In recent years, deep learning (DL) has shown great potential in the field of dermatological image analysis. However, existing datasets in this domain have significant limitations,…
Discriminator-free Unsupervised Domain Adaptation for Multi-label Image Classification
Indel Pal Singh, Enjie Ghorbel, Anis Kacem +2
In this paper, a discriminator-free adversarial-based Unsupervised Domain Adaptation (UDA) for Multi-Label Image Classification (MLIC) referred to as DDA-MLIC is proposed. Recently…
Multi-label Image Classification using Adaptive Graph Convolutional Networks: from a Single Domain to Multiple Domains
Indel Pal Singh, Enjie Ghorbel, Oyebade Oyedotun +1
This paper proposes an adaptive graph-based approach for multi-label image classification. Graph-based methods have been largely exploited in the field of multi-label classificatio…
LSPnet: A 2D Localization-oriented Spacecraft Pose Estimation Neural Network
Albert Garcia, Mohamed Adel Musallam, Vincent Gaudilliere +4
Being capable of estimating the pose of uncooperative objects in space has been proposed as a key asset for enabling safe close-proximity operations such as space rendezvous, in-or…
Vertex Feature Encoding and Hierarchical Temporal Modeling in a Spatial-Temporal Graph Convolutional Network for Action Recognition
Konstantinos Papadopoulos, Enjie Ghorbel, Djamila Aouada +1
This paper extends the Spatial-Temporal Graph Convolutional Network (ST-GCN) for skeleton-based action recognition by introducing two novel modules, namely, the Graph Vertex Featur…
Localized Trajectories for 2D and 3D Action Recognition
Konstantinos Papadopoulos, Girum Demisse, Enjie Ghorbel +3
The Dense Trajectories concept is one of the most successful approaches in action recognition, suitable for scenarios involving a significant amount of motion. However, due to nois…