The significant power of deep learning networks has led to enormous development in object
detection. Over the last few years, object detector frameworks have achieved tremendous …

For autonomous vehicles to be able to operate successfully they need to be aware of other
vehicles with sufficient time to make safe, stable plans. Given the possible closing speeds …

Autonomous vehicle (AV) systems rely on robust perception models as a cornerstone of
safety assurance. However objects encountered on the road exhibit a long-tailed distribution …

Abstract According to the Wall Street Journal, one billion surveillance cameras will be
deployed around the world by 2021. This amount of information can be hardly managed by …

Manual annotation of bounding boxes for object detection in digital images is tedious, and
time and resource consuming. In this paper, we propose a semi-automatic method for …

遮挡目标检测长期以来是计算机视觉中的一个难点和研究热点. 目前的深度学习基于卷积神经
网络, 将目标检测任务作为分类任务和回归任务来处理. 当目标被遮挡时, 遮挡物会混淆目标之间 …

Deep learning requires large amounts of annotated data. Manual annotation of objects in
video is, regardless of annotation type, a tedious and time-consuming process. In particular …

We consider a class of variable effort human annotation tasks in which the number of labels
required per item can greatly vary (eg, finding all faces in an image, named entities in a text …

Periodic cleaning of all frequently touched social areas such as walls, doors, locks, handles,
windows has become the first line of defense against all infectious diseases. Among those …

Automated factories use deep-learning-based vision systems to accurately detect various
products. However, training such vision systems requires manual annotation of a significant …