Object Detection in Video using Faster R-CNN
نویسنده
چکیده
Convolutional neural networks (CNN) currently dominate the computer vision landscape. Recently, a CNN based model, Faster R-CNN [1], achieved stateof-the-art performance at object detection on the PASCAL VOC 2007 and 2012 datasets. It combines region proposal generation with object detection on a single frame in less than 200ms. We apply the Faster R-CNN model to video clips from the ImageNet 2015 Object Detection from Video challenge [2]. By leveraging additional temporal information from the video, we ranked 3rd place in terms of mean average precision. This work is being presented as a poster at the ICCV 2015 ImageNet and MS COCO Visual Recognition Challenges Joint Workshop.
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