Datasets:

gexinh
/

UltraVR

	---
	license: other
	license_name: mixed-research-only
	task_categories:
	- visual-question-answering
	- image-to-text
	language:
	- en
	pretty_name: UltraVR
	tags:
	- ultra-resolution
	- ultra-high-resolution
	- visual-reasoning
	- evidence-grounded-reasoning
	- visual-question-answering
	- vision-language-models
	- multimodal-reasoning
	- remote-sensing
	- surveillance
	- industrial-anomaly-detection
	- anomaly-detection
	---

	# UltraVR

	UltraVR is a diagnostic ultra-resolution image VQA benchmark for evidence-grounded reasoning across remote sensing, CCTV surveillance, and industrial anomaly detection domains.

	This repository is a data-only release. It provides benchmark QA annotations, selected redistributable AD images, source mapping files for non-redistributed image domains, and license notices.

	Keywords: ultra-resolution image understanding; ultra-high-resolution visual reasoning; evidence-grounded reasoning; visual question answering; vision-language models; multimodal reasoning; remote sensing; CCTV surveillance; industrial anomaly detection.

	## QA-Only Annotation Release

	This trial version keeps the final question, options, answer, question type, one `image_path`, image dimensions, and license notes. No chain-of-thought is included. In JSONL records, AD `image_path` values point to local files in this repository, while RS and CCTV `image_path` values point to the original source-dataset image paths.

	## Domain Summary

	\| Domain \| Source Dataset \| Image Files in This Repo \| Mapping File \| Notes \|
	\|---\|---\|---:\|---\|---\|
	\| RS \| DOTA-v1.5 \| No \| `data/images/rs/mapping.csv` \| Raw DOTA images are not redistributed. \|
	\| CCTV \| PANDA \| No \| `data/images/cctv/mapping.csv` \| PANDA is treated as high-resolution still images/screenshots. \|
	\| AD \| MVTec LOCO AD \| Yes \| Not required \| User-provided constructed AD images are included. \|

	## Source Datasets

	- RS: DOTA-v1.5, https://captain-whu.github.io/DOTA/dataset.html
	- CCTV: PANDA, https://gigavision.cn/data/news?nav=DataSet%20Panda&type=nav&t=1781477597958
	- AD: MVTec LOCO AD, https://www.mvtec.com/research-teaching/datasets/mvtec-loco-ad

	## Repository Structure

	```text
	UltraVR/
	├── README.md
	├── LICENSE
	├── NOTICE
	├── RELEASE_POLICY.md
	├── DATA_SCHEMA.md
	├── data/
	│ ├── annotations/
	│ │ ├── ultravr_rs.jsonl
	│ │ ├── ultravr_cctv.jsonl
	│ │ ├── ultravr_ad.jsonl
	│ │ └── ultravr_all.jsonl
	│ └── images/
	│ ├── rs/
	│ │ ├── README.md
	│ │ └── mapping.csv
	│ ├── cctv/
	│ │ ├── README.md
	│ │ └── mapping.csv
	│ └── ad/
	│ ├── README.md
	│ └── <AD image files>
	└── examples/
	├── sample_rs.jsonl
	├── sample_cctv.jsonl
	└── sample_ad.jsonl
	```

	## Annotation Files

	All annotations are JSONL files. Each line is one QA sample. `data/annotations/ultravr_all.jsonl` concatenates RS, CCTV, and AD annotations in that order.

	- `data/annotations/ultravr_rs.jsonl`: 120 QA samples
	- `data/annotations/ultravr_cctv.jsonl`: 120 QA samples
	- `data/annotations/ultravr_ad.jsonl`: 140 QA samples
	- `data/annotations/ultravr_all.jsonl`: 380 QA samples

	## License

	UltraVR follows a mixed research-only licensing policy. Users must follow the original license and usage terms of each source dataset. See `LICENSE`, `NOTICE`, and `RELEASE_POLICY.md` for details.

	## Citation

	If you use UltraVR in your research, please cite our paper:

	UltraVR: A Diagnostic Ultra-Resolution Image-VQA Benchmark for Evidence-Grounded Reasoning
	Gexin Huang, Yanting Yang, Myeongkyun Kang, Beidi Zhao, Jun Zhou, Chen Zhou, Gang Wang, Zu-hua Gao, and Xiaoxiao Li.
	arXiv:2606.05576, 2026.

	```bibtex
	@misc{huang2026ultravr,
	title = {UltraVR: A Diagnostic Ultra-Resolution Image-VQA Benchmark for Evidence-Grounded Reasoning},
	author = {Huang, Gexin and Yang, Yanting and Kang, Myeongkyun and Zhao, Beidi and Zhou, Jun and Zhou, Chen and Wang, Gang and Gao, Zu-hua and Li, Xiaoxiao},
	year = {2026},
	eprint = {2606.05576},
	archivePrefix = {arXiv},
	primaryClass = {cs.CV},
	doi = {10.48550/arXiv.2606.05576},
	url = {https://arxiv.org/abs/2606.05576}
	}
	```

	Please also cite the original source datasets used by the corresponding UltraVR domains, including DOTA-v1.5, PANDA, and MVTec LOCO AD, when applicable.