activity
20182022
most citedMask-Guided Attention Network for Occluded Pedestrian Detection

36 citations · 67 across the 3 of their papers we have counts for

collaborators

9 papers

cs.CV2023

Multiclass Confidence and Localization Calibration for Object Detection

Bimsara Pathiraja, Malitha Gunawardhana, Muhammad Haris Khan

Albeit achieving high predictive accuracy across many challenging computer vision problems, recent studies suggest that deep neural networks (DNNs) tend to make overconfident predi…

cs.CV20227 cited

Towards Improving Calibration in Object Detection Under Domain Shift

Muhammad Akhtar Munir, Muhammad Haris Khan, M. Saquib Sarfraz +1

With deep neural network based solution more readily being incorporated in real-world applications, it has been pressing requirement that predictions by such models, especially in…

cs.CV2022

Generative Cooperative Learning for Unsupervised Video Anomaly Detection

Muhammad Zaigham Zaheer, Arif Mahmood, Muhammad Haris Khan +3

Video anomaly detection is well investigated in weakly-supervised and one-class classification (OCC) settings. However, unsupervised video anomaly detection methods are quite spars…

cs.CV20217 cited

Synergizing between Self-Training and Adversarial Learning for Domain Adaptive Object Detection

Muhammad Akhtar Munir, Muhammad Haris Khan, M. Saquib Sarfraz +1

We study adapting trained object detectors to unseen domains manifesting significant variations of object appearance, viewpoints and backgrounds. Most current methods align domains…

cs.CV201924 cited

Deep Contextual Attention for Human-Object Interaction Detection

Tiancai Wang, Rao Muhammad Anwer, Muhammad Haris Khan +4

Human-object interaction detection is an important and relatively new class of visual relationship detection tasks, essential for deeper scene understanding. Most existing approach…

cs.CV201936 cited

Mask-Guided Attention Network for Occluded Pedestrian Detection

Yanwei Pang, Jin Xie, Muhammad Haris Khan +3

Pedestrian detection relying on deep convolution neural networks has made significant progress. Though promising results have been achieved on standard pedestrians, the performance…