--- license: apache-2.0 task_categories: - image-segmentation task_ids: - semantic-segmentation pretty_name: SynPASS tags: - panoramic-vision - autonomous-driving - semantic-segmentation - synthetic - 360-degree - cvpr-2022 --- # SynPASS: Synthetic Panoramic Semantic Segmentation Benchmark Official Dataset Repository for the **SynPASS** benchmark (Trans4PASS / Trans4PASS+). - **GitHub Repository:** https://github.com/InSAI-Lab/Trans4PASS - **Paper (Trans4PASS, CVPR 2022):** [arXiv:2203.01452](https://arxiv.org/abs/2203.01452) - **Paper (Trans4PASS+, arXiv 2022):** [arXiv:2207.11860](https://arxiv.org/abs/2207.11860) - **Model Checkpoints:** [InSAI-Lab/Trans4PASS](https://huggingface.co/InSAI-Lab/Trans4PASS) --- ## Dataset Description The **SynPASS** dataset contains **9,080** panoramic images (1024x2048) across **22** semantic categories. The dataset covers diverse scenarios: - Weather: Cloudy, Foggy, Rainy, Sunny - Lighting: Day-time, Night-time ### Statistics | Condition | Cloudy | Foggy | Rainy | Sunny | Total | | :--- | :---: | :---: | :---: | :---: | :---: | | **Split (train/val/test)** | 1420/420/430 | 1420/430/420 | 1420/430/420 | 1440/410/420 | 5700/1690/1690 | | **Split (day/night)** | 1980/290 | 1710/560 | 2040/230 | 1970/300 | 7700/1380 | | **Total Frames** | 2270 | 2270 | 2270 | 2270 | **9080** | ## File Structure The dataset archive `SynPASS.tar.gz` (~4.8 GB) unpacks into: ```text SynPASS/ ├── img/ │ ├── cloud/ │ ├── fog/ │ ├── rain/ │ └── sun/ └── semantic/ ├── cloud/ ├── fog/ ├── rain/ └── sun/ ``` ## Quick Start & Download Using the Hugging Face CLI: ```bash # Download dataset archive hf download InSAI-Lab/SynPASS SynPASS.tar.gz --type dataset --local-dir ./datasets # Extract archive cd ./datasets tar -zxvf SynPASS.tar.gz ``` Using Python (`huggingface_hub`): ```python from huggingface_hub import hf_hub_download dataset_path = hf_hub_download( repo_id="InSAI-Lab/SynPASS", repo_type="dataset", filename="SynPASS.tar.gz", local_dir="./datasets" ) ``` ## Citation ```bibtex @inproceedings{zhang2022bending, title={Bending Reality: Distortion-aware Transformers for Adapting to Panoramic Semantic Segmentation}, author={zhang, Jiaming and Yang, Kailun and Ma, Chaoxiang and Rei{\ss}, Simon and Peng, Kunyu and Stiefelhagen, Rainer}, booktitle={CVPR}, pages={16917--16927}, year={2022} } @article{zhang2022behind, title={Behind Every Domain There is a Shift: Adapting Distortion-aware Vision Transformers for Panoramic Semantic Segmentation}, author={Zhang, Jiaming and Yang, Kailun and Shi, Hao and Rei{\ss}, Simon and Peng, Kunyu and Ma, Chaoxiang and Fu, Haodong and Wang, Kaiwei and Stiefelhagen, Rainer}, journal={arXiv preprint arXiv:2207.11860}, year={2022} } ``` ## License This dataset is released under the [Apache-2.0 License](https://www.apache.org/licenses/LICENSE-2.0).