Khurram Azeem Hashmi

"Object Detection in Challenging Environments"

As one of the most fundamental and challenging problems in computer vision, object detection has received noticeable attention in recent years. Deep learning has boosted generic object detection by providing remarkable breakthroughs in several domains ranging from historical document images to crowded videos. This research focuses on developing a unified object detection-based framework that operates under various challenging domains.
In this talk, I will present the proposed object detection-based frameworks that have shown superior results in a couple of domains, i.e., scanned documents and floor plan images. Furthermore, I will demonstrate the effectiveness of current object detection algorithms by benchmarking them on challenging vision datasets. The talk will conclude with a brief discussion on the future directions.

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