CVPR 2020之ReID：Cross-modality Person re-identification with Shared-Specific Feature Transfer
Cross-modality Person re-identification with Shared-Specific Feature Transfer 当前的问题及概述： 现有的研究主要集中在通过将不同的模态嵌入到同一个特征空间中来学习共同的表达。然而，只学习共同特征意味着巨大的信息损失，降低了特征的差异性。 在本文中，提出了一种新的跨模态共享特征转移算法(cm-SSFT)来解决上述问题，以探
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相关文章
- 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——论文周报
- 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)——论文阅读
- 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论文分类汇总清单
- 10. CVPR 2020-Object Detection