GCNet
Single Image Reflection Removal based on GAN with Gradient Constraint (GCNet) (by ryo-abiko)
ERRNet
Single Image Reflection Removal Exploiting Misaligned Training Data and Network Enhancements (CVPR 2019) (by Vandermode)
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The number of mentions indicates the total number of mentions that we've tracked plus the number of user suggested alternatives.
Stars - the number of stars that a project has on GitHub. Growth - month over month growth in stars.
Activity is a relative number indicating how actively a project is being developed. Recent commits have higher weight than older ones.
For example, an activity of 9.0 indicates that a project is amongst the top 10% of the most actively developed projects that we are tracking.
Stars - the number of stars that a project has on GitHub. Growth - month over month growth in stars.
Activity is a relative number indicating how actively a project is being developed. Recent commits have higher weight than older ones.
For example, an activity of 9.0 indicates that a project is amongst the top 10% of the most actively developed projects that we are tracking.
GCNet
Posts with mentions or reviews of GCNet.
We have used some of these posts to build our list of alternatives
and similar projects. The last one was on 2021-10-13.
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Remove Reflections from Cars
GCNET(https://github.com/ryo-abiko/GCNet) This method uses a GAN to remove reflections from single images. This method provided similar results to Obstruction removal. It reduced brightness in some areas. I feel this technique is more catered to removing white light reflections from the glass. I tried passing in only the car window images to this network. The reflections in the glass were still present. A few highlighted areas had reduced brightness.
ERRNet
Posts with mentions or reviews of ERRNet.
We have used some of these posts to build our list of alternatives
and similar projects. The last one was on 2021-10-13.
-
Remove Reflections from Cars
ERRNet (https://github.com/Vandermode/ERRNet) This model was trained on single image pairs with reflective images and GT images. Running some samples from our dataset provided results that were not promising. Most of the reflections were still present.
What are some alternatives?
When comparing GCNet and ERRNet you can also consider the following projects:
ObstructionRemoval - [CVPR 2020] Learning to See Through Obstructions