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dkalsan/FLEDGE

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Hugging Face2026-04-20 更新2026-04-26 收录
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--- license: gpl-3.0 task_categories: - image-segmentation tags: - semantic-segmentation - synthetic-data - domain-adaptation - cityscapes - acdc size_categories: - 100K<n<1M --- ## Dataset Summary This dataset contains generated images for semantic segmentation targeting the **Cityscapes** and **ACDC** domains. The images are produced from five source datasets using the method described in: [A Framework for Low-Effort Training Data Generation for Urban Semantic Segmentation](https://arxiv.org/abs/2510.11567). ## Technical Specifications * **Subset Selection:** To preserve storage space, we release the **top 3 generated images** per original source image, selected based on our proposed **MCOC score**. * **Label Mapping:** All masks follow the standard **Cityscapes 19-class format**. * **Resolution:** 512 x 1024 (Height x Width). * **Format:** Images and masks are provided in `.png` format. --- ## Dataset Statistics The following table reflects the number of source images used to generate the target domain data. | Source Domain | Image Count | Status | | :--- | :--- | :--- | | **GTA** | 24,966 | Available | | **UrbanSyn** | 7,539 | Available | | **VEIS** | 3,018 | Available | | **SHIFT** | 3,000 | Available | | **Synscapes** | 0 | Restricted | > **Note on Synscapes:** Due to licensing restrictions, we are unable to release the generated Synscapes data. The folders contain the original license file for reference but do not include image data. --- ## Dataset Structure The data is organized by `<Target_Domain>/<Source_Domain>/`. ```text <Target_Domain>/ └── <Source_Domain>/ ├── images/ # Top 3 generated images per source (MCOC ranked) ├── original_tid/ # Original source segmentation maps ├── hrda_tid/ # HRDA pseudo-labels ├── splits/ # .txt files for training loading └── LICENSE # Original source dataset license ``` --- ## Usage Example Example data loading scripts that utilize the provided .txt split files are available in our official GitHub repository: [github.com/vislearn/FLEDGE](https://github.com/vislearn/FLEDGE) --- ## Citation ```text @misc{kalsan2025fledge, title={A Framework for Low-Effort Training Data Generation for Urban Semantic Segmentation}, author={Damjan Kalšan and Denis Zavadski and Tim Küchler and Haebom Lee and Stefan Roth and Carsten Rother}, year={2025}, eprint={2510.11567}, archivePrefix={arXiv}, primaryClass={cs.CV} } ```
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