Circle-Based Ratio Loss for Person Reidentification
المؤلفون المشاركون
Yang, Zhao
Liu, Jiehao
Liu, Tie
Wang, Li
Zhao, Sai
المصدر
العدد
المجلد 2020، العدد 2020 (31 ديسمبر/كانون الأول 2020)، ص ص. 1-11، 11ص.
الناشر
Hindawi Publishing Corporation
تاريخ النشر
2020-12-29
دولة النشر
مصر
عدد الصفحات
11
التخصصات الرئيسية
الملخص EN
Person reidentification (re-id) aims to recognize a specific pedestrian from uncrossed surveillance camera views.
Most re-id methods perform the retrieval task by comparing the similarity of pedestrian features extracted from deep learning models.
Therefore, learning a discriminative feature is critical for person reidentification.
Many works supervise the model learning with one or more loss functions to obtain the discriminability of features.
Softmax loss is one of the widely used loss functions in re-id.
However, traditional softmax loss inherently focuses on the feature separability and fails to consider the compactness of within-class features.
To further improve the accuracy of re-id, many efforts are conducted to shrink within-class discrepancy as well as between-class similarity.
In this paper, we propose a circle-based ratio loss for person re-identification.
Concretely, we normalize the learned features and classification weights to map these vectors in the hypersphere.
Then we take the ratio of the maximal intraclass distance and the minimal interclass distance as an objective loss, so the between-class separability and within-class compactness can be optimized simultaneously during the training stage.
Finally, with the joint training of an improved softmax loss and the ratio loss, the deep model could mine discriminative pedestrian information and learn robust features for the re-id task.
Comprehensive experiments on three re-id benchmark datasets are carried out to illustrate the effectiveness of the proposed method.
Specially, 83.12% mAP on Market-1501, 71.70% mAP on DukeMTMC-reID, and 66.26%/63.24% mAP on CUHK03 labeled/detected are achieved, respectively.
نمط استشهاد جمعية علماء النفس الأمريكية (APA)
Yang, Zhao& Liu, Jiehao& Liu, Tie& Wang, Li& Zhao, Sai. 2020. Circle-Based Ratio Loss for Person Reidentification. Complexity،Vol. 2020, no. 2020, pp.1-11.
https://search.emarefa.net/detail/BIM-1145868
نمط استشهاد الجمعية الأمريكية للغات الحديثة (MLA)
Yang, Zhao…[et al.]. Circle-Based Ratio Loss for Person Reidentification. Complexity No. 2020 (2020), pp.1-11.
https://search.emarefa.net/detail/BIM-1145868
نمط استشهاد الجمعية الطبية الأمريكية (AMA)
Yang, Zhao& Liu, Jiehao& Liu, Tie& Wang, Li& Zhao, Sai. Circle-Based Ratio Loss for Person Reidentification. Complexity. 2020. Vol. 2020, no. 2020, pp.1-11.
https://search.emarefa.net/detail/BIM-1145868
نوع البيانات
مقالات
لغة النص
الإنجليزية
الملاحظات
Includes bibliographical references
رقم السجل
BIM-1145868
قاعدة معامل التأثير والاستشهادات المرجعية العربي "ارسيف Arcif"
أضخم قاعدة بيانات عربية للاستشهادات المرجعية للمجلات العلمية المحكمة الصادرة في العالم العربي
تقوم هذه الخدمة بالتحقق من التشابه أو الانتحال في الأبحاث والمقالات العلمية والأطروحات الجامعية والكتب والأبحاث باللغة العربية، وتحديد درجة التشابه أو أصالة الأعمال البحثية وحماية ملكيتها الفكرية. تعرف اكثر