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Real-Time MDNet
Cited 144 time in
Web of Science
Cited 69 time in Scopus
- Authors
- Issue Date
- 2018
- Publisher
- SPRINGER INTERNATIONAL PUBLISHING AG
- Citation
- COMPUTER VISION - ECCV 2018, PT IV, Vol.11208, pp.89-104
- Abstract
- We present a fast and accurate visual tracking algorithm based on the multi-domain convolutional neural network (MDNet). The proposed approach accelerates feature extraction procedure and learns more discriminative models for instance classification; it enhances representation quality of target and background by maintaining a high resolution feature map with a large receptive field per activation. We also introduce a novel loss term to differentiate foreground instances across multiple domains and learn a more discriminative embedding of target objects with similar semantics. The proposed techniques are integrated into the pipeline of a well known CNN-based visual tracking algorithm, MDNet. We accomplish approximately 25 times speed-up with almost identical accuracy compared to MDNet. Our algorithm is evaluated in multiple popular tracking benchmark datasets including OTB2015, UAV123, and TempleColor, and outperforms the state-of-the-art real-time tracking methods consistently even without dataset-specific parameter tuning.
- ISSN
- 0302-9743
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