1 citations · 1 across the 1 of their papers we have counts for
3 papers
NullSpaceNet: Nullspace Convoluional Neural Network with Differentiable Loss Function
Mohamed H. Abdelpakey, Mohamed S. Shehata
We propose NullSpaceNet, a novel network that maps from the pixel level input to a joint-nullspace (as opposed to the traditional feature space), where the newly learned joint-null…
DomainSiam: Domain-Aware Siamese Network for Visual Object Tracking
Mohamed H. Abdelpakey, Mohamed S. Shehata
Visual object tracking is a fundamental task in the field of computer vision. Recently, Siamese trackers have achieved state-of-the-art performance on recent benchmarks. However, S…
DensSiam: End-to-End Densely-Siamese Network with Self-Attention Model for Object Tracking
Mohamed H. Abdelpakey, Mohamed S. Shehata, Mostafa M. Mohamed
Convolutional Siamese neural networks have been recently used to track objects using deep features. Siamese architecture can achieve real time speed, however it is still difficult…