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Visual Object Tracking with Discriminative Filters and Siamese Networks: A Survey and Outlook
[article]
2021
arXiv
pre-print
Accurate and robust visual object tracking is one of the most challenging and fundamental computer vision problems. It entails estimating the trajectory of the target in an image sequence, given only its initial location, and segmentation, or its rough approximation in the form of a bounding box. Discriminative Correlation Filters (DCFs) and deep Siamese Networks (SNs) have emerged as dominating tracking paradigms, which have led to significant progress. Following the rapid evolution of visual
arXiv:2112.02838v1
fatcat:nsre4b5uafeopjb37go6c3obwu