CVPR 2020之ReID：Cross-modality Person re-identification with Shared-Specific Feature Transfer
Cross-modality Person re-identification with Shared-Specific Feature Transfer 當前的問題及概述： 現有的研究主要集中在通過將不同的模態嵌入到同一個特徵空間中來學習共同的表達。然而，只學習共同特徵意味着巨大的信息損失，降低了特徵的差異性。 在本文中，提出了一種新的跨模態共享特徵轉移算法(cm-SSFT)來解決上述問題，以探
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相關文章
- 1. 2019 CVPR之ReID：Towards Rich Feature Discovery with Class Activation Maps Augmentation for Person Re-
- 2. Cross-modality Person re-identification with Shared-Specific Feature Transfer——論文週報
- 3. Arbitrary Style Transfer with Deep Feature Reshuffle
- 4. CVPR 2017:Large Margin Object Tracking with Circulant Feature Maps
- 5. Two-Stage Peer-Regularized Feature Recombination for Arbitrary Image Style Transfer(CVPR 2020)——論文閱讀
- 6. 2019 CVPR之ReID：Densely Semantically Aligned Person Re-Identification
- 7. Re-ID: Learning Deep Feature Representation with Domain Guided Dropout for Person Re-identifiation
- 8. 2020 CVPR 之ReID：AD-Cluster: Augmented Discriminative Clustering for Domain Adaptive Person Re-identi
- 9. CVPR 2020之117篇GAN論文分類彙總清單
- 10. CVPR 2020-Object Detection