| --- |
| license: mit |
| task_categories: |
| - image-segmentation |
| tags: |
| - wsss |
| - boundary-refinement |
| - priors |
| --- |
| |
| # PASCAL VOC 2012 NAMLab Priors for HGA |
|
|
| This dataset repository hosts the pre-computed hierarchical invariant region partition priors for weakly supervised semantic segmentation (WSSS), generated using the NAMLab framework. |
|
|
| These priors serve as the 2D structural guidance stream for the **HGA (Hierarchical-Geometric Alignment)** boundary internalization paradigm. |
|
|
| ## 🔗 Main Codebase |
| The complete implementation, environment setup, and training guidelines are available in our official GitHub repository: |
| 👉 **[Uncertainty-42/HGA](https://github.com/Uncertainty-42/HGA)** |
|
|
| ## 📂 Expected Directory Layout |
| Download the `priors_voc.zip` archive (approx. 4.2 GB) and extract its contents into your local PASCAL VOC dataset structure as shown below: |
|
|
| ```text |
| VOCdevkit/VOC2012/ |
| ├── JPEGImages/ # Original source images (.jpg) |
| ├── SegmentationClassAug/ # Ground Truth masks (.png) |
| └── priors/ |
| └── namlab_pt/ # <- Extract zip contents directly here (.pt files) |
| ``` |
|
|
| ## 📥 Extraction Command |
| Navigate to your local `priors/` directory and run: |
| ```bash |
| unzip priors_voc.zip -d namlab_pt/ |
| ``` |
|
|
| ## 📝 Citation & Attribution |
| If you use these priors in your research, please cite both our work and the foundational NAMLab paper: |
|
|
| ```bibtex |
| @article{zheng2021hierarchical, |
| title={Hierarchical Image Segmentation Based on Nonsymmetry and Anti-Packing Pattern Representation Model}, |
| author={Zheng, Yunping and Yang, Bowen and Sarem, Mudar}, |
| journal={IEEE Transactions on Image Processing}, |
| volume={30}, |
| pages={2408--2421}, |
| year={2021}, |
| publisher={IEEE} |
| } |
| ``` |
