T-CNN: Tubelets With Convolutional Neural Networks for Object Detection From Videos

The state-of-the-art performance for object detection has been significantly improved over the past two years. Besides the introduction of powerful deep neural networks, such as GoogleNet and VGG, novel object detection frameworks, such as R-CNN and its successors, Fast R-CNN, and Faster R-CNN, play an essential role in improving the state of the art. Despite their effectiveness on still images, those frameworks are not specifically designed for object detection from videos. Temporal and contextual information of videos are not fully investigated and utilized. In this paper, we propose a deep learning framework that incorporates temporal and contextual information from tubelets obtained in videos, which…

• NN
  National Natural Science Foundation of China

  Award: 61371192
• CP
  China Postdoctoral Science Foundation

  Award: 2014M552339
• OO
  Office of Naval Research

  Award: N00014-15-1-2356