A survey on metric learning for feature vectors and structured data
The need for appropriate ways to measure the distance or similarity between data is
ubiquitous in machine learning, pattern recognition and data mining, but handcrafting such …
ubiquitous in machine learning, pattern recognition and data mining, but handcrafting such …
A tutorial on distance metric learning: Mathematical foundations, algorithms, experimental analysis, prospects and challenges
Distance metric learning is a branch of machine learning that aims to learn distances from
the data, which enhances the performance of similarity-based algorithms. This tutorial …
the data, which enhances the performance of similarity-based algorithms. This tutorial …
Person re-identification by multi-channel parts-based cnn with improved triplet loss function
Person re-identification across cameras remains a very challenging problem, especially
when there are no overlapping fields of view between cameras. In this paper, we present a …
when there are no overlapping fields of view between cameras. In this paper, we present a …
Gated siamese convolutional neural network architecture for human re-identification
Matching pedestrians across multiple camera views, known as human re-identification, is a
challenging research problem that has numerous applications in visual surveillance. With …
challenging research problem that has numerous applications in visual surveillance. With …
[PDF][PDF] Siamese neural networks for one-shot image recognition
G Koch, R Zemel, R Salakhutdinov - ICML deep learning workshop, 2015 - cs.utoronto.ca
The process of learning good features for machine learning applications can be very
computationally expensive and may prove difficult in cases where little data is available. A …
computationally expensive and may prove difficult in cases where little data is available. A …
Frontal to profile face verification in the wild
We have collected a new face data set that will facilitate research in the problem of frontal to
profile face verificationin the wild'. The aim of this data set is to isolate the factor of pose …
profile face verificationin the wild'. The aim of this data set is to isolate the factor of pose …
A siamese long short-term memory architecture for human re-identification
Matching pedestrians across multiple camera views known as human re-identification (re-
identification) is a challenging problem in visual surveillance. In the existing works …
identification) is a challenging problem in visual surveillance. In the existing works …
Compressed video action recognition
Training robust deep video representations has proven to be much more challenging than
learning deep image representations. This is in part due to the enormous size of raw video …
learning deep image representations. This is in part due to the enormous size of raw video …
End-to-end comparative attention networks for person re-identification
Person re-identification across disjoint camera views has been widely applied in video
surveillance yet it is still a challenging problem. One of the major challenges lies in the lack …
surveillance yet it is still a challenging problem. One of the major challenges lies in the lack …
Deepreid: Deep filter pairing neural network for person re-identification
Person re-identification is to match pedestrian images from disjoint camera views detected
by pedestrian detectors. Challenges are presented in the form of complex variations of …
by pedestrian detectors. Challenges are presented in the form of complex variations of …