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20192026
most citedMulti-label Image Classification using Adaptive Graph Convolutional Networks: from a Single Domain to Multiple Domains

23 citations · 51 across the 20 of their papers we have counts for

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Showing 2025Show all

6 papers · 1 filter

cs.CV2025

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…

cs.CV2025★ 1 cited

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…

cs.CV2025★ 2 cited

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…

cs.LG2025

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…

cs.CV2025

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…

cs.CV2025

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…