Add dataset card and documentation for SpatialUAV

README.md

@@ -0,0 +1,90 @@
+---
+license: mit
+task_categories:
+- image-text-to-text
+- video-text-to-text
+tags:
+- uav
+- spatial-intelligence
+- vqa
+---
+
+# SpatialUAV: Benchmarking Spatial Intelligence for Low-Altitude UAV Perception, Collaboration, and Motion
+
+[**Paper**](https://huggingface.co/papers/2606.27876) | [**GitHub**](https://github.com/Hyu-Zhang/SpatialUAV)
+
+**SpatialUAV** is a benchmark for evaluating spatial intelligence in real low-altitude UAV scenarios. It covers perception, spatial relation reasoning, aerial-aerial collaboration, aerial-ground collaboration, and UAV motion understanding under a unified visual-question-answer format.
+
+<p align="center">
+  <img src="https://raw.githubusercontent.com/Hyu-Zhang/SpatialUAV/main/assets/example_vis.png" width="100%" alt="SpatialUAV examples">
+</p>
+
+## Highlights
+
+- **4,331 curated instances** from real low-altitude UAV images, videos, and metadata.
+- **14 task types** across semantic discrimination, spatial relations, aerial-aerial collaboration, aerial-ground collaboration, and motion understanding.
+- **7 visual input configurations** covering single images, paired views, candidate-view selection, annotated images, and ordered video frames.
+- **9 answer formats**, including option labels, region IDs, region pairs, bounding boxes, angle-distance values, movement directions, and free-form text.
+- **Task-specific evaluation** for heterogeneous outputs instead of relying on one generic text metric.
+
+## Benchmark Overview
+
+<p align="center">
+  <img src="https://raw.githubusercontent.com/Hyu-Zhang/SpatialUAV/main/assets/data_pipeline.png" width="100%" alt="SpatialUAV data pipeline">
+</p>
+
+| Group | Instances | Task Types | Main Capability |
+| --- | ---: | --- | --- |
+| Semantic Discrimination | 599 | Region Recognition, Anomaly Detection | Recognize queried objects and safety-critical regions |
+| Spatial Relation | 716 | Direction Recognition, Distance Comparison | Infer direction and relative depth from UAV views |
+| Aerial-Aerial Collaboration | 1,231 | Collaboration Recognition, Shared Association, Object Matching, Camera Transformation, Occlusion Removal | Match and reason across multiple UAV viewpoints |
+| Aerial-Ground Collaboration | 785 | Shared Association, Collaboration Recognition, View Translation, Path Planning | Align aerial and ground observations |
+| Motion Understanding | 1,000 | Global Motion | Describe UAV/camera motion over ordered frames |
+
+## Data Format
+
+The annotation file is JSONL. Each line is one benchmark instance:
+
+```json
+{
+  "id": "Region_Recognition_00001",
+  "image": ["./SpatialUAV/samples_Single_Image/img0001.jpg"],
+  "conversations": [
+    {
+      "from": "human",
+      "value": "Which regions in the image contain a parking lot? Answer with only the region labels, formatted exactly like `Region 1, 2`. No explanation."
+    }
+  ],
+  "source": "SpatialUAV",
+  "GT": "Region 3, 4."
+}
+```
+
+Expected dataset layout after download:
+
+```text
+SpatialUAV/
+  annotations.jsonl
+  annotations_subset_20pct_per_task.jsonl
+  samples_Single_Image/
+  samples_A2A_Pured/
+  samples_A2A_detected/
+  samples_A2A_Occlusion_Removal/
+  samples_A2G_Pured/
+  samples_A2G_detected/
+  samples_A2G_Path_Planning/
+  samples_Motion_Understanding_Frames/
+```
+
+Use `annotations_subset_20pct_per_task.jsonl` for quick checks and `annotations.jsonl` for full benchmark evaluation.
+
+## Citation
+
+```bibtex
+@article{zhang2026spatialuav,
+  title   = {SpatialUAV: Benchmarking Spatial Intelligence for Low-Altitude UAV Perception, Collaboration, and Motion},
+  author  = {Zhang, Haoyu and Liu, Meng and Xiang, Qianlong and Wang, Kun and Wang, Yaowei and Nie, Liqiang},
+  journal = {arXiv preprint arXiv:2606.27876},
+  year    = {2026}
+}
+```