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Exploit the Unknown Gradually: One-Shot Video-Based Person Re-Identification by Stepwise Learning
時間 2021-01-11
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在這篇論文中,作者提出了通過逐漸利用未標註樣本,來解決單標註樣本(one-shot)情況下的視頻行人重識別問題(video-based person re-ID)。這個方法簡單通用,在MARS和DukeMTMC兩個視頻行人重識別數據集上都達到了遠超 state-of-the art 的性能。 1. 論文概述 爲什麼需要關注單標註(one shot)樣本問題? 目前大多行人重識別方法都依賴於完全的數
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【EUG】Exploit the Unknown Gradually: One-Shot Video-Based Person Re-Identification by Stepwise Learn
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相關文章
1.
【EUG】Exploit the Unknown Gradually: One-Shot Video-Based Person Re-Identification by Stepwise Learn
2.
CVPR 2018 行人重識別:Exploit the Unknown Gradually: One-Shot Video-Based Person Re-Identification by S L
3.
Stepwise Metric Promotion for Unsupervised Video Person Re-identification
4.
【FSR】Feature Space Regularization for Person Re-Identification with One Sample
5.
Unsupervised Person Re-identification by Soft Multilabel Learning
6.
Improving Person Re-identification by Attribute and Identity Learning
7.
Unsupervised Person Re-identification by Deep Learning Tracklet Association
8.
Person search: Joint Detection and Identification Feature Learning for Person Search筆記
9.
【Person Re-ID】Person Re-Identification by Deep Learning Multi-Scale Representations
10.
OSCP Learning Notes - Exploit(6)
>>更多相關文章<<