Body: <p>While training i noticed this problem
  pic1
  <a href="https://i.sstatic.net/TQoszZJj.jpg" rel="nofollow noreferrer"><img src="https://i.sstatic.net/TQoszZJj.jpg" alt="pic1" /></a></p>
  <p>pic2
  <a href="https://i.sstatic.net/FyvBTNZV.jpg" rel="nofollow noreferrer"><img src="https://i.sstatic.net/FyvBTNZV.jpg" alt="enter image description here" /></a></p>
  <p>pic3
  <a href="https://i.sstatic.net/UpW5H4ED.jpg" rel="nofollow noreferrer"><img src="https://i.sstatic.net/UpW5H4ED.jpg" alt="enter image description here" /></a></p>
  <p>pic4
  <a href="https://i.sstatic.net/2QRh55M6.jpg" rel="nofollow noreferrer"><img src="https://i.sstatic.net/2QRh55M6.jpg" alt="enter image description here" /></a></p>
  
Comments.ContentLicense: CC BY-SA 4.0
Comments.CreationDate: 2024-06-18T14:10:03.673Z
Comments.Text: it probably depends on too many factors to answer you... architecture, optimization, loss, normalization
Comments.UserDisplayName: Alberto
Comments.ContentLicense: CC BY-SA 4.0
Comments.CreationDate: 2024-06-18T20:22:52.210Z
Comments.Text: so, you mean that there is no intuitive explanation?
Comments.UserDisplayName: Тима 
Comments.ContentLicense: CC BY-SA 4.0
Comments.CreationDate: 2024-06-18T22:13:30.127Z
Comments.Text: I only mean that i hard to give you an educated guess / answer without many more information
Comments.UserDisplayName: Alberto
Tags: <generative-model>
Title: Why vq-vae sometimes struggles with homogenous background?
UserDisplayName: Тима 
ThreadText: # Why vq-vae sometimes struggles with homogenous background?
  
  (Asked by: username_0 on 2024-06-18)
  
  While training i noticed this problem
  pic1
  [![pic1](https://i.sstatic.net/TQoszZJj.jpg)](https://i.sstatic.net/TQoszZJj.jpg)
  
  pic2
  [![enter image description here](https://i.sstatic.net/FyvBTNZV.jpg)](https://i.sstatic.net/FyvBTNZV.jpg)
  
  pic3
  [![enter image description here](https://i.sstatic.net/UpW5H4ED.jpg)](https://i.sstatic.net/UpW5H4ED.jpg)
  
  pic4
  [![enter image description here](https://i.sstatic.net/2QRh55M6.jpg)](https://i.sstatic.net/2QRh55M6.jpg)
  
  **Tags:** generative-model
  > **Comments:**
  > **username_1**: it probably depends on too many factors to answer you... architecture, optimization, loss, normalization  
  > **username_0**: so, you mean that there is no intuitive explanation?  
  > **username_1**: I only mean that i hard to give you an educated guess / answer without many more information  
  
  ---
  
  ## 0 answers
  
  