Answers.Body: <p>Welcome to AI SE! I think they use an <strong>AlexNet architecture</strong> for the following 2 reasons.</p>
  <p><strong>1:</strong> The AlexNet architecture matches exactly with the architecture shown in Figure 3 (5 conv layers and 3 fc layers).</p>
  <p><strong>2:</strong> Looking at the paper, they mention</p>
  <blockquote>
  <p>For all other networks, we use a pretrained AlexNet model</p>
  </blockquote>
  <p>Although they do not specifically state that they use AlexNet for their own work, this was (and is) very common for representation learning papers. In addition, if you use AlexNet for the baseline models, it is very logical to take the same architecture for your new model.</p>
  <p><strong>Kernel sizes/strides:</strong> Seeing both their reference to AlexNet and the matching architecture, I would assume they use AlexNet for their own architecture as well. Please see the <a href="https://www.wikiwand.com/en/AlexNet#:%7E:text=AlexNet%20is%20the%20name%20of,Krizhevsky%27s%20Ph.D.%20advisor." rel="nofollow noreferrer">AlexNet wikipedia</a> figure for an easy overview of the kernel-sizes/strides of AlexNet.</p>
  
Answers.ContentLicense: CC BY-SA 4.0
Answers.CreationDate: 2023-05-08T08:09:17.897Z
Answers.LastActivityDate: 2023-05-08T08:09:17.897Z
Answers.UserDisplayName: Robin van Hoorn
Body: <p>I am trying to implement the paper <a href="https://arxiv.org/abs/1704.01719" rel="nofollow noreferrer">Beyond triplet loss: a deep quadruplet network for person re-identification</a>. In the paper, they provide a figure (attached below) containing the network architecture, but they don't specify the exact kernel sizes.</p>
  <p><a href="https://i.sstatic.net/q5r3A.png" rel="nofollow noreferrer"><img src="https://i.sstatic.net/q5r3A.png" alt="enter image description here" /></a></p>
  <p>Can anyone help with getting the exact network architecture? Thanks in advance.</p>
  
Tags: <deep-neural-networks><architecture><triplet-loss-function>
Title: What architecture is used for deep quadruplet network for person re-identification
UserDisplayName: Varghese Kuruvilla
ThreadText: # What architecture is used for deep quadruplet network for person re-identification
  
  (Asked by: username_0 on 2023-05-08)
  
  I am trying to implement the paper [Beyond triplet loss: a deep quadruplet network for person re-identification](https://arxiv.org/abs/1704.01719). In the paper, they provide a figure (attached below) containing the network architecture, but they don't specify the exact kernel sizes.
  
  [![enter image description here](https://i.sstatic.net/q5r3A.png)](https://i.sstatic.net/q5r3A.png)
  
  Can anyone help with getting the exact network architecture? Thanks in advance.
  
  **Tags:** deep-neural-networks, architecture, triplet-loss-function
  
  ---
  
  ## 1 answers
  
  ### Answer by username_1 on 2023-05-08. Score: 2
  
  Welcome to AI SE! I think they use an **AlexNet architecture** for the following 2 reasons.
  
  **1:** The AlexNet architecture matches exactly with the architecture shown in Figure 3 (5 conv layers and 3 fc layers).
  
  **2:** Looking at the paper, they mention
  
  > For all other networks, we use a pretrained AlexNet model
  
  Although they do not specifically state that they use AlexNet for their own work, this was (and is) very common for representation learning papers. In addition, if you use AlexNet for the baseline models, it is very logical to take the same architecture for your new model.
  
  **Kernel sizes/strides:** Seeing both their reference to AlexNet and the matching architecture, I would assume they use AlexNet for their own architecture as well. Please see the [AlexNet wikipedia](https://www.wikiwand.com/en/AlexNet#:%7E:text=AlexNet%20is%20the%20name%20of,Krizhevsky%27s%20Ph.D.%20advisor.) figure for an easy overview of the kernel-sizes/strides of AlexNet.
  
  
  ---
  
  