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 learning-based methods for person re-identification: A comprehensive review
D Wu, SJ Zheng, XP Zhang, CA Yuan, F Cheng… - Neurocomputing, 2019 - Elsevier
In recent years, person re-identification (ReID) has received much attention since it is a
fundamental task in intelligent surveillance systems and has widespread application …
fundamental task in intelligent surveillance systems and has widespread application …
TBE-Net: A three-branch embedding network with part-aware ability and feature complementary learning for vehicle re-identification
Vehicle re-identification (Re-ID) is one of the promising applications in the field of computer
vision. Existing vehicle Re-ID methods mainly focus on global appearance features or pre …
vision. Existing vehicle Re-ID methods mainly focus on global appearance features or pre …
Unsupervised person re-identification by soft multilabel learning
Although unsupervised person re-identification (RE-ID) has drawn increasing research
attentions due to its potential to address the scalability problem of supervised RE-ID models …
attentions due to its potential to address the scalability problem of supervised RE-ID models …
Learning with average precision: Training image retrieval with a listwise loss
Image retrieval can be formulated as a ranking problem where the goal is to order database
images by decreasing similarity to the query. Recent deep models for image retrieval have …
images by decreasing similarity to the query. Recent deep models for image retrieval have …
In defense of the triplet loss for person re-identification
In the past few years, the field of computer vision has gone through a revolution fueled
mainly by the advent of large datasets and the adoption of deep convolutional neural …
mainly by the advent of large datasets and the adoption of deep convolutional neural …
Pose-driven deep convolutional model for person re-identification
Feature extraction and matching are two crucial components in person Re-Identification
(ReID). The large pose deformations and the complex view variations exhibited by the …
(ReID). The large pose deformations and the complex view variations exhibited by the …
Deeply-learned part-aligned representations for person re-identification
In this paper, we address the problem of person re-identification, which refers to associating
the persons captured from different cameras. We propose a simple yet effective human part …
the persons captured from different cameras. We propose a simple yet effective human part …
Deep metric learning with hierarchical triplet loss
W Ge - Proceedings of the European conference on …, 2018 - openaccess.thecvf.com
We present a novel hierarchical triplet loss (HTL) capable of automatically collecting
informative training samples (triplets) via a defined hierarchical tree that encodes global …
informative training samples (triplets) via a defined hierarchical tree that encodes global …
Attention-aware compositional network for person re-identification
Person re-identification (ReID) is to identify pedestrians observed from different camera
views based on visual appearance. It is a challenging task due to large pose variations …
views based on visual appearance. It is a challenging task due to large pose variations …