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2019 TCSVT之ReID:SDL: Spectrum-Disentangled Representation Learning for Visible-Infrared Person Re-id
時間 2021-01-07
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SDL: Spectrum-Disentangled Representation Learning for Visible-Infrared Person Re-identificatio 當前的問題及概述: 現有的RGB-IR ReID模型側重於通過共享特徵嵌入、子空間學習或對抗性學習來彌補RGB與IR圖像之間的差距。然而,這些方法並沒有明確地忽略與ReID無關的頻譜信息。此外,對抗性學習方法
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相關文章
1.
【ReID】Hierarchical and Efficient Learning for Person Re-Identification
2.
論文筆記23 -- (ReID)Receptive Multi-granularity Representation for Person Re-Identification
3.
2019 IET之ReID:HPILN: a feature learning framework for cross-modality person re-identification
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6.
【ReID】【Skimming】Unsupervised Cross-Dataset Transfer Learning for Person Re-identification
7.
【PLPR】Progressive Learning for Person Re-Identification with One Example
8.
Learning Context Graph for Person Search
9.
View Confusion Feature Learning for Person Re-identification
10.
ReID簡記-3-3D PersonVLAD: Learning Deep Global Representations for Video-based Person Re-id
>>更多相關文章<<