Details

Autor(en) / Beteiligte

• Tumrani, Saifullah
• Ali, Wazir
• Kumar, Rajesh
• Khan, Abdullah Aman
• Dharejo, Fayaz Ali

Titel

View-aware attribute-guided network for vehicle re-identification

Ist Teil von

• Multimedia systems, 2023-08, Vol.29 (4), p.1853-1863

Ort / Verlag

Berlin/Heidelberg: Springer Berlin Heidelberg

Erscheinungsjahr

2023

Quelle

Alma/SFX Local Collection

Beschreibungen/Notizen

• Vehicle re-identification is one of the essential application of urban surveillance. Due to enormous variation in inter-class and intra-class resemblance creates a challenge for methods to distinguish between the same vehicles. Additionally, varying illumination and complex environments create significant hurdles for the existing methods to re-identify vehicles. We present a multi-guided learning method in this paper that uses multi-attribute and view point information, while also enhancing the robustness of feature extraction. The multi-attribute sub-network learns discriminative features like, i.e. color and type of vehicle. Moreover, the view predictor network adds extra information to the feature embedding and To validate the effectiveness of our framework, experiments on two benchmark datasets VeRi-776 and VehicleID are conducted. Experimental results illustrate our framework achieved comparative performance.