【FSR】Feature Space Regularization for Person Re-Identification with One Sample

時間 2021-01-11

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Feature Space Regularization for Person Re-Identification with One Sample Abstract I. INTRODUCTION Framework. Our Method. II. RELATED WORKS A. Supervised Re-ID B. Semi-supervised Re-ID C. Unsupervised

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1. 【PLPR】Progressive Learning for Person Re-Identification with One Example
2. Re-ID: Learning Deep Feature Representation with Domain Guided Dropout for Person Re-identifiation
3. 【VSA】One-shot video-based person re-identification with variance subsampling algorithm
4. READING NOTE: Learning Spatial Regularization with Image-level Supervisions for Multi-label ...
5. SSPP-DAN: DEEP DOMAIN ADAPTATION NETWORK FOR FACE RECOGNITION WITH SINGLE SAMPLE PER PERSON
6. Local Generic Representation for Face Recognition with Single Sample per Person (ACCV, 2014)
7. ZOJ_3329 One Person Game
8. 2019 CVPR之ReID：Towards Rich Feature Discovery with Class Activation Maps Augmentation for Person Re-
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10. Person search: Joint Detection and Identification Feature Learning for Person Search筆記
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1. 【PLPR】Progressive Learning for Person Re-Identification with One Example
2. Re-ID: Learning Deep Feature Representation with Domain Guided Dropout for Person Re-identifiation
3. 【VSA】One-shot video-based person re-identification with variance subsampling algorithm
4. READING NOTE: Learning Spatial Regularization with Image-level Supervisions for Multi-label ...
5. SSPP-DAN: DEEP DOMAIN ADAPTATION NETWORK FOR FACE RECOGNITION WITH SINGLE SAMPLE PER PERSON
6. Local Generic Representation for Face Recognition with Single Sample per Person (ACCV, 2014)
7. ZOJ_3329 One Person Game
8. 2019 CVPR之ReID：Towards Rich Feature Discovery with Class Activation Maps Augmentation for Person Re-
9. 1707.Deep Learning for Person Reidentification Using Support Vector Machines 論文筆記
10. Person search: Joint Detection and Identification Feature Learning for Person Search筆記

>>更多相關文章<<