Tag: VOT-RGBT Challenge
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Won VOT-RGBT Challenge at ICCV 2019
Lichao Zhang won the VOT-RGBT challenge this year. His work is published in the VOT 2019 workshop:
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Multi-Modal Fusion for End-to-End RGB-T Tracking
Lichao Zhang, Martin Danelljan, Abel Gonzalez-Garcia, Joost van de Weijer, Fahad Shahbaz Khan Read Full Paper → We propose an end-to-end tracking framework for fusing the RGB and TIR modalities in RGB-T tracking. Our baseline tracker is DiMP (Discriminative Model Prediction), which employs a carefully designed target prediction network trained end-to-end using a discriminative loss. We analyze the effectiveness […]