7 citations · 14 across the 12 of their papers we have counts for
14 papers · 1 filter
Domain Adaptive Object Detection via Balancing Between Self-Training and Adversarial Learning
Muhammad Akhtar Munir, Muhammad Haris Khan, M. Saquib Sarfraz +1
Deep learning based object detectors struggle generalizing to a new target domain bearing significant variations in object and background. Most current methods align domains by usi…
Leveraging Topology for Domain Adaptive Road Segmentation in Satellite and Aerial Imagery
Javed Iqbal, Aliza Masood, Waqas Sultani +1
Getting precise aspects of road through segmentation from remote sensing imagery is useful for many real-world applications such as autonomous vehicles, urban development and plann…
Detection and Localization of Firearm Carriers in Complex Scenes for Improved Safety Measures
Arif Mahmood, Abdul Basit, M. Akhtar Munir +1
Detecting firearms and accurately localizing individuals carrying them in images or videos is of paramount importance in security, surveillance, and content customization. However,…
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…
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…
Learning from Scale-Invariant Examples for Domain Adaptation in Semantic Segmentation
M. Naseer Subhani, Mohsen Ali
Self-supervised learning approaches for unsupervised domain adaptation (UDA) of semantic segmentation models suffer from challenges of predicting and selecting reasonable good qual…