Similarity has always been a key aspect in computer science and statistics. Any time two
element vectors are compared, many different similarity approaches can be used …

Deep reinforcement learning augments the reinforcement learning framework and utilizes
the powerful representation of deep neural networks. Recent works have demonstrated the …

In the image fusion field, the design of deep learning-based fusion methods is far from
routine. It is invariably fusion-task specific and requires a careful consideration. The most …

We propose an online tracking algorithm that performs the object detection and data
association under a common framework, capable of linking objects after a long time span …

Recently, combining multiple features into discriminative correlation filters to improve
tracking representation has shown great potential in object tracking. Existing trackers apply …

Siamese-based trackers have achieved excellent performance on visual object tracking.
However, the target template is not updated online, and the features of target template and …

摘要目标跟踪一直以来都是计算机视觉领域的关键问题, 最近随着人工智能技术的飞速发展,
运动目标跟踪问题得到了越来越多的关注. 本文对主流目标跟踪算法进行了综述, 首先 …

Abstract We present Siam R-CNN, a Siamese re-detection architecture which unleashes the
full power of two-stage object detection approaches for visual object tracking. We combine …

In the era of rapid development of artificial intelligence, the integration of multimedia and
human-artificial intelligence has become an important research hotspot. Especially in the …

Current state-of-the-art trackers rely only on a target appearance model in order to localize
the object in each frame. Such approaches are however prone to fail in case of eg fast …