Feature pyramid attention (FPA) modules
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Description
We should look into the feature pyramid attention (FPA) module for pixel-precise attention for segmentation features extracted from our resnet encoder.
> Pyramid Attention Network for Semantic Segmentation
https://arxiv.org/abs/1805.10180
_from https://arxiv.org/abs/1805.10180 Figure 2_
_from https://arxiv.org/abs/1805.10180 Figure 3_
The GAU modules could be interesting to try out instead of our simple decoder modules, too.
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
Start by reading the referenced Pyramid Attention Network for Semantic Segmentation paper, then inspect the ResNet encoder and existing simple decoder modules. Determine the intended FPA integration points and whether GAU modules are also in scope. Done should mean a defined implementation and evaluation plan for pixel-precise segmentation attention.
Written by the indexing model from the issue text.
Assessment
- Tech stack
- python
- Domain
- machine-learning
- Issue type
- Feature
- Difficulty
- 5/5
- Estimated time
- Over a week
- Activity status
- Stale
- Clarity
- Needs clarification
- Newbie friendliness
- 30/100