4 citations · 4 across the 4 of their papers we have counts for
4 papers
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…
Cal-DETR: Calibrated Detection Transformer
Muhammad Akhtar Munir, Salman Khan, Muhammad Haris Khan +2
Albeit revealing impressive predictive performance for several computer vision tasks, deep neural networks (DNNs) are prone to making overconfident predictions. This limits the ado…
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,…
Bridging Precision and Confidence: A Train-Time Loss for Calibrating Object Detection
Muhammad Akhtar Munir, Muhammad Haris Khan, Salman Khan +1
Deep neural networks (DNNs) have enabled astounding progress in several vision-based problems. Despite showing high predictive accuracy, recently, several works have revealed that…