Multi-Level Joint Feature Learning for Person Re-Identification
نویسندگان
چکیده
منابع مشابه
Joint Dimension Reduction and Metric Learning for Person Re-identification
Person re-identification is an important technique towards automatic search of a person’s presence in a surveillance video. Among various methods developed for person re-identification, the Mahalanobis metric learning approaches have attracted much attention due to their impressive performance. In practice, many previous papers have applied the Principle Component Analysis (PCA) for dimension r...
متن کاملJoint Learning for Attribute-Consistent Person Re-Identification
Person re-identification has recently attracted a lot of attention in the computer vision community. This is in part due to the challenging nature of matching people across cameras with different viewpoints and lighting conditions, as well as across human pose variations. The literature has since devised several approaches to tackle these challenges, but the vast majority of the work has been c...
متن کاملHierarchical Invariant Feature Learning with Marginalization for Person Re-Identification
This paper addresses the problem of matching pedestrians across multiple camera views, known as person re-identification. Variations in lighting conditions, environment and pose changes across camera views make re-identification a challenging problem. Previous methods address these challenges by designing specific features or by learning a distance function. We propose a hierarchical feature le...
متن کاملMulti-Level Factorisation Net for Person Re-Identification
Key to effective person re-identification (Re-ID) is modelling discriminative and view-invariant factors of person appearance at both high and low semantic levels. Recently developed deep Re-ID models either learn a holistic single semantic level feature representation and/or require laborious human annotation of these factors as attributes. We propose Multi-Level Factorisation Net (MLFN), a no...
متن کاملView-Adaptive Metric Learning for Multi-view Person Re-identification
Person re-identification is a challenging problem due to drastic variations in viewpoint, illumination and pose. Most previous works on metric learning learn a global distance metric to handle those variations. Different from them, we propose a view-adaptive metric learning (VAML) method, which adopts different metrics adaptively for different image pairs under varying views. Specifically, give...
متن کاملذخیره در منابع من
با ذخیره ی این منبع در منابع من، دسترسی به آن را برای استفاده های بعدی آسان تر کنید
ژورنال
عنوان ژورنال: Algorithms
سال: 2020
ISSN: 1999-4893
DOI: 10.3390/a13050111