Optical Flow using deep learning

username: DimTrigkakis
cooked: <p>Hello,</p>
<p>Are there any projects on pytorch that compute optical flow? This would probably be based on current research, where optical flow is computed using deep learning. I have not been able to find any pytorch code related to this, nor any pretrained models regarding this issue.</p>

username: Milton_Wong
cooked: <aside class="quote no-group" data-username="DimTrigkakis" data-post="1" data-topic="4767">
<div class="title">
<div class="quote-controls"></div>
<img loading="lazy" alt="" width="24" height="24" src="https://discuss.pytorch.org/user_avatar/discuss.pytorch.org/dimtrigkakis/48/1094_2.png" class="avatar"> DimTrigkakis:</div>
<blockquote>
<p>pytorch</p>
</blockquote>
</aside>
<p>I think you mean the flownet model. It has quite some pytorch implementation</p><aside class="onebox allowlistedgeneric" data-onebox-src="https://github.com/ClementPinard/FlowNetPytorch">
  <header class="source">
      <img src="https://github.githubassets.com/favicons/favicon.svg" class="site-icon" width="32" height="32">

      <a href="https://github.com/ClementPinard/FlowNetPytorch" target="_blank" rel="noopener nofollow ugc">GitHub</a>
  </header>

  <article class="onebox-body">
    <div class="aspect-image" style="--aspect-ratio:690/344;"><img src="https://opengraph.githubassets.com/a9b3ecc07f87b4f0d6d2ebaa1a0c5157463125e024eb5bd443c9c6272402bcba/ClementPinard/FlowNetPytorch" class="thumbnail" width="690" height="345"></div>

<h3><a href="https://github.com/ClementPinard/FlowNetPytorch" target="_blank" rel="noopener nofollow ugc">GitHub - ClementPinard/FlowNetPytorch: Pytorch implementation of FlowNet by...</a></h3>

  <p>Pytorch implementation of FlowNet by Dosovitskiy et al. - GitHub - ClementPinard/FlowNetPytorch: Pytorch implementation of FlowNet by Dosovitskiy et al.</p>


  </article>

  <div class="onebox-metadata">
    
    
  </div>

  <div style="clear: both"></div>
</aside>


username: myx
cooked: <p>You can use the latest RAFT published on ECCV, the model currently performs best on the sintel dataset<br>
</p><aside class="onebox whitelistedgeneric">
  <header class="source">
      <img src="https://github.githubassets.com/favicons/favicon.svg" class="site-icon" width="32" height="32">
      <a href="https://github.com/princeton-vl/RAFT" target="_blank" rel="nofollow noopener">GitHub</a>
  </header>
  <article class="onebox-body">
    <img src="https://avatars2.githubusercontent.com/u/29677746?s=400&amp;v=4" class="thumbnail onebox-avatar" width="420" height="420">

<h3><a href="https://github.com/princeton-vl/RAFT" target="_blank" rel="nofollow noopener">princeton-vl/RAFT</a></h3>

<p>Contribute to princeton-vl/RAFT development by creating an account on GitHub.</p>


  </article>
  <div class="onebox-metadata">
    
    
  </div>
  <div style="clear: both"></div>
</aside>


username: Federico_Vasile
cooked: <p>Hi there, I’m interested too in optical flow, but I’m looking for a solution that is able to compute optical flow in real-time (i.e. I have an input video stream and I need to compute optical flow as the frames arrive), does anyone know anything about? Or maybe suggestions/workarounds.<br>
All the solutions that I found compute optical flow as a pre-processing step, which is not suitable for my case.<br>
Thank you <img src="https://discuss.pytorch.org/images/emoji/apple/slight_smile.png?v=9" title=":slight_smile:" class="emoji" alt=":slight_smile:"></p>