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What is Bhat Learning Discriminative Model Prediction For Tracking ICCV 2019 Paper about?

This document presents a novel end-to-end trainable tracking architecture that enhances visual tracking by incorporating both target and background appearance information, overcoming limitations of traditional Siamese methods. The proposed model utilizes a discriminative learning loss and an iterative optimization process to achieve superior discriminative power and robustness, setting new state-of-the-art results across multiple tracking benchmarks. The architecture operates efficiently at over 40 FPS, dem

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plei.pltr

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EN