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 ### OceanPlus
 **[[Paper]](https://arxiv.org/pdf/2008.02745v2.pdf) [[Raw Results]](https://drive.google.com/drive/folders/1doQiv82swum2rEXXo5C735WrLb_uAVbq?usp=sharing) [[Training and Testing Tutorial]](https://github.com/researchmm/TracKit/tree/master/lib/tutorial/OceanPlus/oceanplus.md) [[Demo]](https://github.com/researchmm/TracKit/tree/master/demo/oceanplus.gif)** <br/>
 Official implementation of the OceanPlus tracker. It proposes an attention retrieval network (ARN) to perform soft spatial constraints on backbone features. Concretely, we first build a look-up-table (LUT) with the ground-truth mask in the starting frame, and then retrieve the LUT to obtain a target-aware attention map for suppressing the negative influence of pixel-wise background clutter. Furthermore, we introduce a multi-resolution multi-stage segmentation network (MMS) to ulteriorly weaken responses of background clutter by reusing the predicted mask to filter backbone features.
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 <img src="https://github.com/researchmm/TracKit/blob/master/demo/oceanplu_overview.png" height="250" alt="OceanPlus"/><br/>
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 ## How To Start