Siamese neural networks: An overview
D Chicco - Artificial neural networks, 2021 - Springer
Similarity has always been a key aspect in computer science and statistics. Any time two
element vectors are compared, many different similarity approaches can be used …
element vectors are compared, many different similarity approaches can be used …
Deep learning for person re-identification: A survey and outlook
Person re-identification (Re-ID) aims at retrieving a person of interest across multiple non-
overlapping cameras. With the advancement of deep neural networks and increasing …
overlapping cameras. With the advancement of deep neural networks and increasing …
Deep metric learning: A survey
M Kaya, HŞ Bilge - Symmetry, 2019 - mdpi.com
Metric learning aims to measure the similarity among samples while using an optimal
distance metric for learning tasks. Metric learning methods, which generally use a linear …
distance metric for learning tasks. Metric learning methods, which generally use a linear …
Joint discriminative and generative learning for person re-identification
Person re-identification (re-id) remains challenging due to significant intra-class variations
across different cameras. Recently, there has been a growing interest in using generative …
across different cameras. Recently, there has been a growing interest in using generative …
Multi-similarity loss with general pair weighting for deep metric learning
A family of loss functions built on pair-based computation have been proposed in the
literature which provide a myriad of solutions for deep metric learning. In this pa-per, we …
literature which provide a myriad of solutions for deep metric learning. In this pa-per, we …
Pose-guided feature alignment for occluded person re-identification
Persons are often occluded by various obstacles in person retrieval scenarios. Previous
person re-identification (re-id) methods, either overlook this issue or resolve it based on an …
person re-identification (re-id) methods, either overlook this issue or resolve it based on an …
Mixed high-order attention network for person re-identification
Attention has become more attractive in person re-identification (ReID) as it is capable of
biasing the allocation of available resources towards the most informative parts of an input …
biasing the allocation of available resources towards the most informative parts of an input …
Learning discriminative features with multiple granularities for person re-identification
G Wang, Y Yuan, X Chen, J Li, X Zhou - Proceedings of the 26th ACM …, 2018 - dl.acm.org
The combination of global and partial features has been an essential solution to improve
discriminative performances in person re-identification (Re-ID) tasks. Previous part-based …
discriminative performances in person re-identification (Re-ID) tasks. Previous part-based …
Visual attention methods in deep learning: An in-depth survey
Inspired by the human cognitive system, attention is a mechanism that imitates the human
cognitive awareness about specific information, amplifying critical details to focus more on …
cognitive awareness about specific information, amplifying critical details to focus more on …
A bottom-up clustering approach to unsupervised person re-identification
Most person re-identification (re-ID) approaches are based on supervised learning, which
requires intensive manual annotation for training data. However, it is not only …
requires intensive manual annotation for training data. However, it is not only …