1 citations · 1 across the 3 of their papers we have counts for
3 papers
cs.CV2025
xMOD: Cross-Modal Distillation for 2D/3D Multi-Object Discovery from 2D motion
Saad Lahlali, Sandra Kara, Hejer Ammar +4
Object discovery, which refers to the task of localizing objects without human annotations, has gained significant attention in 2D image analysis. However, despite this growing int…
cs.CV2023★ 1 cited
The Background Also Matters: Background-Aware Motion-Guided Objects Discovery
Sandra Kara, Hejer Ammar, Florian Chabot +1
Recent works have shown that objects discovery can largely benefit from the inherent motion information in video data. However, these methods lack a proper background processing, r…
cs.CV2022
Image Segmentation-based Unsupervised Multiple Objects Discovery
Sandra Kara, Hejer Ammar, Florian Chabot +1
Unsupervised object discovery aims to localize objects in images, while removing the dependence on annotations required by most deep learning-based methods. To address this problem…