Topology-aware loss function for combined pixel-wise and topology loss
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- Dominant language
- Python
- Stars
- 2.1k
- Forks
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Description
At the moment we are using pixel-wise loss functions for our segmentation models. These loss functions are great for overall segmentation problems but they fail to capture topology inherent in our satellite imagery.
One example use-case is roads. The pixel-wise loss functions don't penalize for connectivity issues.
We should look into topological-aware loss functions to help with these problems and to directly optimize for example for connectivity instead of having to do a much more difficult task in post-processing.
Idea:
- look into https://arxiv.org/abs/1712.02190 https://arxiv.org/abs/1603.08155
- try out a combined loss `a * pixelwise + b * topology`
Contributor guide
First steps
- Read the whole issue, then the project's contributing guide.
- Comment on the issue to say you are picking it up — it saves two people doing the same work.
- Fork the repository and make your change on a branch.
- Open a pull request that references the issue number.
Research direction
No files, tests, or entry points are named. Start by reading the two linked papers, then inspect how the repository currently defines and applies pixel-wise segmentation losses. Done means evaluating a topology-aware loss combined as `a * pixelwise + b * topology` for improved connectivity.
Written by the indexing model from the issue text.
Assessment
- Tech stack
- python
- Domain
- computer-vision, machine-learning
- Issue type
- Feature
- Difficulty
- 5/5
- Estimated time
- Over a week
- Activity status
- Stale
- Clarity
- Needs clarification
- Newbie friendliness
- 25/100