UA-DETRAC is a challenging real-world multi-object detection and multi-object tracking benchmark. The dataset consists of 10 hours of videos captured with a Cannon EOS 550D camera at 24 different locations at Beijing and Tianjin in China. The videos are recorded at 25 frames per seconds (fps), with resolution of 960×540 pixels. There are more than 140 thousand frames in the UA-DETRAC dataset and 8250 vehicles that are manually annotated, leading to a total of 1.21 million labeled bounding boxes of objects. We also perform benchmark tests of state-of-the-art methods in object detection and multi-object tracking, together with evaluation metrics detailed in this website.
* The deadline for submission is over, thanks for participating in our AVSS2017 Challenge!
* UA-DETRAC challenge is now partner with NVIDIA AI City Challenge!