2 citations · 3 across the 7 of their papers we have counts for
4 papers · 1 filter
TOOD: Task-Aware Out-of-Distribution Score Calibration for Continual Learners
Mostafa ElAraby, Samer B. Nashed, Liam Paull
The primary challenge of continual learning (CL) systems is to learn new tasks while remaining performant on previously learned tasks. A similarly important though less well-studie…
BACS: Background Aware Continual Semantic Segmentation
Mostafa ElAraby, Ali Harakeh, Liam Paull
Semantic segmentation plays a crucial role in enabling comprehensive scene understanding for robotic systems. However, generating annotations is challenging, requiring labels for e…
GROOD: GRadient-Aware Out-of-Distribution Detection
Mostafa ElAraby, Sabyasachi Sahoo, Yann Pequignot +2
Out-of-distribution (OOD) detection is crucial for ensuring the reliability of deep learning models in real-world applications. Existing methods typically focus on feature represen…
Ghost on the Shell: An Expressive Representation of General 3D Shapes
Zhen Liu, Yao Feng, Yuliang Xiu +4
The creation of photorealistic virtual worlds requires the accurate modeling of 3D surface geometry for a wide range of objects. For this, meshes are appealing since they 1) enable…