May 22, 2019 · Abstract:Vehicle Re-ID has recently attracted enthusiastic attention due to its potential applications in smart city and urban surveillance.
Attribute-Guided Feature Learning Network for Vehicle Reidentification
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Jun 2, 2020 · This article proposes a novel attribute-guided network (AGNet), which learns global representation with the abundant attribute features in an end-to-end manner.
To handle these issues, in this paper, we propose a novel deep network architecture, which guided by meaningful attributes including camera views, vehicle types ...
Jan 12, 2020 · This paper proposes a novel Attribute-Guided Network (AGNet), which could learn global representation with the abundant attribute features in an end-to-end ...
This article proposes a novel attribute-guided network (AGNet), which learns global representation with the abundant attribute features in an end-to-end manner.
Missing: Attributes Re- Identification.
To handle these issues, in this paper, we propose a novel deep network architecture, which guided by meaningful attributes including camera views, vehicle types ...
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To handle these issues, in this paper, we propose a novel deep network architecture, which guided by meaningful attributes including camera views, vehicle types ...
Vehicle re-identification is one of the core technologies of intelligent transportation systems and smart cities, but large intra-class diversity and ...
Apr 8, 2024 · AIVR-Net learns identity representations and visual-attribute invariant representations by multi-task training strategy.
Mar 29, 2023 · The multi-attribute sub-network learns discriminative features like, i.e. color and type of vehicle. Moreover, the view predictor network adds ...