| --- |
| language: |
| - en |
| license: cc-by-4.0 |
| task_categories: |
| - image-text-to-text |
| - visual-question-answering |
| pretty_name: SenseBench |
| tags: |
| - remote-sensing |
| - image-quality-assessment |
| - benchmark |
| --- |
| |
| # SenseBench |
|
|
| [**SenseBench: A Benchmark for Remote Sensing Low-Level Visual Perception and Description in Large Vision-Language Models**](https://huggingface.co/papers/2605.10576) |
|
|
| 🏠 [GitHub](https://github.com/Zhong-Chenchen/SenseBench) | 🤗 [Hugging Face Fullset](https://huggingface.co/datasets/Zhongchenchen/SenseBench) |
|
|
| ## Overview |
|
|
| SenseBench is the first dedicated diagnostic benchmark for remote sensing (RS) low-level visual perception and description. Driven by a physics-based hierarchical taxonomy, SenseBench features over 10K meticulously curated instances across 6 major and 22 fine-grained RS degradation categories. |
|
|
| The benchmark evaluates Vision-Language Models (VLMs) through two complementary protocols: |
| - **SensePerception**: Objective low-level visual perception (using What/Whether/How questions). |
| - **SenseDescription**: Subjective diagnostic description focusing on completeness, correctness, and faithfulness. |
|
|
| ## Supported Tasks |
|
|
| - Visual Question Answering |
| - Image-to-Text / Text Generation |
| - Image Quality Assessment |
|
|
| ## Language |
|
|
| - English |
|
|
| ## Data format |
|
|
| Each example contains image paths, a question, an answer, and metadata describing the distortion type. |
|
|
| ```json |
| { |
| "id": "4fda312e-70d2-4df7-b1f7-2f06955bf338", |
| "images": [ |
| "images/4fda312e-70d2-4df7-b1f7-2f06955bf338_0.png", |
| "images/4fda312e-70d2-4df7-b1f7-2f06955bf338_1.png" |
| ], |
| "question": "Using the options provided, rate the overall quality of Image 2 compared to Image 1. |
| A.No/Slight distortion |
| B.Moderate distortion |
| C.Severe distortion", |
| "answer": "A", |
| "meta": { |
| "image_count": "multi", |
| "modality": "RGB", |
| "task": "how", |
| "domain": "general", |
| "distortion_family": "blur", |
| "distortion_type": "blur_gaussian", |
| "distortion_complexity": "single", |
| "comparison": "intra-image" |
| } |
| } |
| ``` |
|
|
| ## Citation |
|
|
| If you use SenseBench in your research, please cite: |
|
|
| ```bibtex |
| @article{zhong2026sensebench, |
| title={SenseBench: A Benchmark for Remote Sensing Low-Level Visual Perception and Description in Large Vision-Language Models}, |
| author={Zhong, Chenchen and others}, |
| journal={arXiv preprint arXiv:2605.10576}, |
| year={2026} |
| } |
| ``` |
