Better Quantifying the Performance of Object Detection in Video



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Better Quantifying the Performance of Object Detection in Video

Object detection is now one of the most common applications in computer vision, especially as vanilla classification problems have become easier to solve with modern deep learning architectures. Due to the wide availability of large-scale datasets (e.g., COCO [1]), object detection research has become more accessible to the computer vision community, leading to technical advancements at a staggering pace. As object detection has become more deeply studied, parallel research has arisen on the topic of performing object detection in video. Such a…

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