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README.md
@@ -49,9 +49,8 @@ Multiple Object Tracking in Deep Learning Approaches:A Survey [[paper](https://w
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<a id="markdown-2022" name="2022"></a>
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### **2022**
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-**P3AFormer**: Tracking Objects as Pixel-wise Distributions [[code](https://sjtuytc.github.io/zelin_pages/p3aformer.html)] [[paper](https://arxiv.org/pdf/2207.05518.pdf)] **ECCV2022 oral**
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-Simple Cues Lead to a Strong Multi-Object Tracker [[code]()] [[paper](https://arxiv.org/pdf/2206.04656.pdf)]
+**P3AFormer**: Tracking Objects as Pixel-wise Distributions [[code](https://sjtuytc.github.io/zelin_pages/p3aformer.html)] [[paper](https://arxiv.org/pdf/2207.05518.pdf)]**ECCV2022 oral**
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**BoT-SORT**: BoT-SORT: Robust Associations Multi-Pedestrian Tracking [[code](https://github.com/NirAharon/BOT-SORT)] [[paper](https://arxiv.org/pdf/2206.14651.pdf)]
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AltStyle によって変換されたページ (->オリジナル) / アドレス: モード: デフォルト 音声ブラウザ ルビ付き 配色反転 文字拡大 モバイル
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