Answers.Body: <p>in computer vision sparse annotations are images for which only a bunch of pixels are annotated. The term sparse in fact is used as in linear algebra, where a sparse matrix indicate a matrix composed mostly of zeros (in this case zeros meaning no label given).</p>
  <p>The idea is that is takes much less time to label just a bunch of pixels rather than entire images. This annotations of course can't be use to train models on fully supervised learning tasks, since classic supervised losses require dense annotations.</p>
  <p>So this type of annotations are instead used in <a href="https://en.wikipedia.org/wiki/Weak_supervision" rel="nofollow noreferrer">weakly supervised learning</a>, a combination of unsupervised techniques combined with constrains coming from the sparse annotations, or in <a href="https://en.wikipedia.org/wiki/Active_learning_(machine_learning)" rel="nofollow noreferrer">active learning</a> set ups, as a staring point to generate automatically dense annotations from sparse ones, to then only use the automatically generate dense annotations for a classic supervised training.</p>
  <p><a href="https://i.sstatic.net/VlixQ.png" rel="nofollow noreferrer"><img src="https://i.sstatic.net/VlixQ.png" alt="dense vs sparse annotations" /></a></p>
  
Answers.ContentLicense: CC BY-SA 4.0
Answers.CreationDate: 2022-03-17T22:22:13.827Z
Answers.LastActivityDate: 2022-03-17T22:22:13.827Z
Answers.UserDisplayName: Edoardo Guerriero
Body: <p>What is exactly sparse annotation? Is it different from labeling images?</p>
  <p>I've been reading a paper about vessel segmentation and have some issues understanding this part.</p>
  
Comments.ContentLicense: CC BY-SA 4.0
Comments.CreationDate: 2022-03-17T22:25:13.357Z
Comments.Text: Can you please provide the name of and link to the paper that you mention in this post, in order for us to have more context?
Comments.UserDisplayName: nbro
Tags: <deep-learning><convolutional-neural-networks><deep-neural-networks><image-processing><image-segmentation>
Title: What is exactly sparse annotation?
UserDisplayName: Kiana Kazeminejad
ThreadText: # What is exactly sparse annotation?
  
  (Asked by: username_0 on 2022-03-17)
  
  What is exactly sparse annotation? Is it different from labeling images?
  
  I've been reading a paper about vessel segmentation and have some issues understanding this part.
  
  **Tags:** deep-learning, convolutional-neural-networks, deep-neural-networks, image-processing, image-segmentation
  > **Comments:**
  > **username_1**: Can you please provide the name of and link to the paper that you mention in this post, in order for us to have more context?  
  
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  ## 1 answers
  
  ### Answer by username_2 on 2022-03-17. Score: 1 | Accepted answer
  
  in computer vision sparse annotations are images for which only a bunch of pixels are annotated. The term sparse in fact is used as in linear algebra, where a sparse matrix indicate a matrix composed mostly of zeros (in this case zeros meaning no label given).
  
  The idea is that is takes much less time to label just a bunch of pixels rather than entire images. This annotations of course can't be use to train models on fully supervised learning tasks, since classic supervised losses require dense annotations.
  
  So this type of annotations are instead used in [weakly supervised learning](https://en.wikipedia.org/wiki/Weak_supervision), a combination of unsupervised techniques combined with constrains coming from the sparse annotations, or in [active learning](https://en.wikipedia.org/wiki/Active_learning_(machine_learning)) set ups, as a staring point to generate automatically dense annotations from sparse ones, to then only use the automatically generate dense annotations for a classic supervised training.
  
  [![dense vs sparse annotations](https://i.sstatic.net/VlixQ.png)](https://i.sstatic.net/VlixQ.png)
  
  
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