Mar 5, 2021 · In this work, we propose a new central feature learning framework for unsuper- vised person RE-ID to improve central feature learning ...
Abstract. The Exemplar Memory (EM) design has shown its effectiveness in facilitating the unsupervised person re-identification (RE-ID).
Abstract: The Exemplar Memory (EM) design has shown its effectiveness in facilitating the unsupervised person re-identification (RE-ID).
People also ask
What is unsupervised feature learning?
What is feature selection for unsupervised machine learning?
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 ...
In this paper, we propose an unsupervised approach for the person re-identification problem based on utilization of Generative Adversarial Network.
Missing: Central | Show results with:Central
Apr 21, 2022 · Our purification modules are proven to be very effective for unsupervised person re-identification. Extensive experiments on three popular person re- ...
Missing: Central | Show results with:Central
We propose a conceptually simple yet effective and learnable module effective block, named the meta feature transformer (MFT).
Missing: Central | Show results with:Central
Jun 1, 2024 · In this article, we study out a method to combine hard instance contrast and cluster contrast, that is, the central feature vector in each ...
Person re-identification (re-ID) is an important topic in computer vision. This paper studies the unsupervised set- ting of re-ID, which does not require ...
Awesome Unsupervised person re-identification is a computer vision task that involves identifying and matching individuals across different non-overlapping ...