73 citations · 89 across the 4 of their papers we have counts for
4 papers
UNICON: Combating Label Noise Through Uniform Selection and Contrastive Learning
Nazmul Karim, Mamshad Nayeem Rizve, Nazanin Rahnavard +2
Supervised deep learning methods require a large repository of annotated data; hence, label noise is inevitable. Training with such noisy data negatively impacts the generalization…
Exploring Complementary Strengths of Invariant and Equivariant Representations for Few-Shot Learning
Mamshad Nayeem Rizve, Salman Khan, Fahad Shahbaz Khan +1
In many real-world problems, collecting a large number of labeled samples is infeasible. Few-shot learning (FSL) is the dominant approach to address this issue, where the objective…
In Defense of Pseudo-Labeling: An Uncertainty-Aware Pseudo-label Selection Framework for Semi-Supervised Learning
Mamshad Nayeem Rizve, Kevin Duarte, Yogesh S Rawat +1
The recent research in semi-supervised learning (SSL) is mostly dominated by consistency regularization based methods which achieve strong performance. However, they heavily rely o…
Gabriella: An Online System for Real-Time Activity Detection in Untrimmed Security Videos
Mamshad Nayeem Rizve, Ugur Demir, Praveen Tirupattur +5
Activity detection in security videos is a difficult problem due to multiple factors such as large field of view, presence of multiple activities, varying scales and viewpoints, an…