Apr 7, 2023 · Unsupervised domain adaptive person re-identification (UDA Re-ID) aims at obtaining more robust and discriminative feature on unlabeled ...
Unsupervised domain adaptive person re-identification (UDA Re-. ID) aims at obtaining more robust and discriminative feature on unlabeled target domain by ...
In recent years, jointly utilizing local and global features to improve model performance is becoming an important approach for person re-identification. If the ...
Our proposed method achieves better performance comparing with the state-of-the-art approaches in common UDA Re-ID tasks, and the mAP gain is up to on the ...
May 19, 2022 · We propose a Learning Feature Fusion (LF2) framework for adaptively learning to fuse global and local features to obtain a more comprehensive fusion feature ...
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What is multi source domain adaptation?
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Therefore, we put forward an unsupervised multi-source domain adaptation (UMDA) method for person re-ID via feature fusion and pseudo-label refinement.
An Intermediate Domain Module (IDM) is proposed to generate intermediate domains' representations on-the-fly by mixing the source and target domains ' ...
The IDM module can be plugged at any hid- den stage of a network, which will generate intermediate domains' representations on-the-fly to gradually bridge the.
In this paper, a multi-level-attention embedding and multi-layer-feature fusion (MEMF) model is proposed for person re-ID.
Based on person fusion features, this paper introduces feature memory to store the fused target features and designs a cross-domain invariance loss function to ...