| --- |
| license: mit |
| task_categories: |
| - image-segmentation |
| - visual-question-answering |
| language: |
| - en |
| tags: |
| - panoramic-vision |
| - active-perception |
| - referring-segmentation |
| - 360-degree |
| - spatial-reasoning |
| size_categories: |
| - 1K<n<10K |
| pretty_name: Active Panoramic Referring Segmentation |
| --- |
| |
| # APRS Dataset |
|
|
| [](https://arxiv.org/abs/2607.02497v1) |
| [](https://henghuiding.com/APRS/) |
| [](https://github.com/FudanCVL/APRS) |
|
|
| ## Dataset Description |
|
|
| **APRS (Active Panoramic Referring Segmentation)** is a large-scale benchmark dataset for active perception in 360° panoramic environments. Unlike passive referring segmentation that processes static images, APRS requires agents to **actively explore** continuous panoramic scenes by adjusting viewing directions to seek and segment targets based on natural language instructions. |
|
|
| ### Dataset Summary |
|
|
| - 🎯 **7,420 samples** across **4,971 diverse panoramic scenes** |
| - 🏠 Indoor and outdoor 360° environments |
| - 📐 **Four types of spatial referring expressions**: |
| - **Egocentric**: First-person directional references (e.g., "look left to find...") |
| - **Unique-Attribute**: Distinctive object features (e.g., "the red sofa") |
| - **Allocentric**: Third-person spatial relations (e.g., "the chair near the window") |
| - **Multi-hop**: Complex relational reasoning (e.g., "look to the left to find the bed, then find the lamp on the table next to it") |
|
|
|
|
| ## Data Fields |
|
|
| Each sample contains: |
|
|
| - `Filename`: Image filename (panoramic view) |
| - `Img_W`, `Img_H`, `Aspect_Ratio`: Image dimensions and aspect ratio |
| - `Pt_X`, `Pt_Y`: Target point pixel coordinates |
| - `Pt_X_Norm`, `Pt_Y_Norm`: Normalized point coordinates [0, 1] |
| - `Box_X`, `Box_Y`, `Box_W`, `Box_H`: Bounding box (x, y, width, height) in pixels |
| - `Box_X_Norm`, `Box_Y_Norm`, `Box_W_Norm`, `Box_H_Norm`: Normalized bounding box [0, 1] |
| - `Pt_Theta`, `Pt_Phi`: Target point spherical coordinates (degrees) |
| - Theta (θ): Horizontal angle [-180°, 180°] |
| - Phi (φ): Vertical angle [-90°, 90°] |
| - `Box_Theta`, `Box_Phi`: Bounding box center spherical coordinates (degrees) |
| - `Description`: Natural language referring expression |
| - `Category`: Spatial reference type |
| - `EGO`: Egocentric (first-person directional) |
| - `ALLO`: Allocentric (third-person spatial relations) |
| - `UNIQ`: Unique attributes |
| - `MULT`: Multi-hop reasoning |
|
|
| ## Usage |
|
|
| ### Load with APRS Dataset Class |
|
|
| ```python |
| from aprs import APRSDataset |
| |
| # Load directly from HuggingFace Hub |
| dataset = APRSDataset.from_hub(repo_id="FudanCVL/APRS_dataset", split="train") |
| |
| # Access samples |
| sample = dataset[0] |
| print(f"Instruction: {sample.instruction}") |
| print(f"Category: {sample.category}") |
| print(f"Initial view: θ={sample.init_theta:.1f}°, φ={sample.init_phi:.1f}°") |
| print(f"Target view: θ={sample.target_theta:.1f}°, φ={sample.target_phi:.1f}°") |
| |
| # Load panoramic image (BGR numpy array) |
| image = sample.load_image() |
| |
| # Get bounding box |
| box_pixels = sample.box_pixels() # (x, y, w, h) in pixels |
| ``` |
|
|
|
|
| ### Interactive 360° Visualization |
|
|
| ```bash |
| # Clone the official repository |
| git clone https://github.com/FudanCVL/APRS.git |
| cd APRS |
| |
| # Install dependencies |
| pip install -e ".[viewer]" |
| |
| # Launch interactive viewer directly from HuggingFace |
| python tools/viewer_360.py --hf --split test --index 0 |
| |
| # Or download dataset and view locally |
| python tools/viewer_360.py --root APRS_dataset --split test --index 0 |
| ``` |
|
|
| **Viewer Controls**: |
| - 🖱️ Drag mouse to rotate view |
| - ⌨️ WASD or Arrow keys for navigation |
| - R to reset to initial view |
| - 🟩 Green box shows target region |
|
|
| ## Citation |
|
|
| If you use this dataset, please cite: |
|
|
| ```bibtex |
| @article{tang2026seek, |
| title={Seek to Segment: Active Perception for Panoramic Referring Segmentation}, |
| author={Tang, Song and Hu, Shuming and Shuai, Xincheng and Ding, Henghui and Jiang, Yu-Gang}, |
| journal={arXiv preprint arXiv:2607.02497}, |
| year={2026} |
| } |
| ``` |
|
|
| ## Contact |
|
|
| - **Song Tang**: tangsong322@gmail.com |
| - **Henghui Ding**: henghuiding@gmail.com |
|
|
| ## License |
|
|
| This dataset is released under the [MIT License](https://opensource.org/licenses/MIT). |
|
|
| ## Links |
|
|
| - 📄 **Paper**: [arXiv:2607.02497](https://arxiv.org/abs/2607.02497v1) |
| - 🌐 **Project Page**: [https://henghuiding.com/APRS/](https://henghuiding.com/APRS/) |
| - 💻 **Code**: [https://github.com/FudanCVL/APRS](https://github.com/FudanCVL/APRS) |
|
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