---
license: apache-2.0
task_categories:
  - object-detection
language:
  - en
tags:
  - referring-expression-comprehension
  - visual-grounding
  - refcocog
  - fine-grained-evaluation
size_categories:
  - 1K<n<10K
---

# RefCOCOg-UMD Test Partitioning

This dataset provides **fine-grained evaluation splits** for the RefCOCOg-UMD test set, designed for Referring Expression Comprehension (REC) tasks. Each sample is partitioned by **difficulty level** and **referential type** to enable more detailed performance analysis.

## Dataset Description

- **Total Samples:** 9,482 (by difficulty) / 19,334 (by referential type, with overlaps)
- **Source:** RefCOCOg-UMD test set
- **Format:** PyTorch `.pth` files

## Data Structure

Each `.pth` file contains a list of tuples with the following structure:

```python
import torch

data = torch.load("Easy.pth")
for item in data:
    img_name, hw_dict, bbox, phrase, obj_mask = item
    # img_name: str - Image filename
    # hw_dict: dict - Height and width info {"height": int, "width": int}
    # bbox: list - Bounding box [x1, y1, x2, y2]
    # phrase: str - Referring expression text
    # obj_mask: tensor/array - Object segmentation mask
```

## File Organization

### By Difficulty Level
- `Easy.pth` - Simple referring expressions (4,109 samples)
- `Medium.pth` - Moderate complexity (4,517 samples)
- `Hard.pth` - Complex expressions (856 samples)

### By Referential Type × Difficulty
- `{Type}_Easy.pth`, `{Type}_Medium.pth`, `{Type}_Hard.pth`
- Types: `Attribute`, `Relation`, `Logic`, `Ambiguity`, `Perspective`

## Statistics for Each File

<table border="1" style="border-collapse: collapse;">
  <tr>
    <th>Filename</th>
    <th>Avg. Length</th>
    <th>Samples</th>
  </tr>
  <tr>
    <td>Attribute_Easy.pth</td>
    <td>35.92</td>
    <td>3,076</td>
  </tr>
  <tr>
    <td>Attribute_Medium.pth</td>
    <td>48.74</td>
    <td>3,431</td>
  </tr>
  <tr>
    <td>Attribute_Hard.pth</td>
    <td>50.90</td>
    <td>563</td>
  </tr>
  <tr>
    <td>Relation_Easy.pth</td>
    <td>37.86</td>
    <td>2,673</td>
  </tr>
  <tr>
    <td>Relation_Medium.pth</td>
    <td>47.51</td>
    <td>4,092</td>
  </tr>
  <tr>
    <td>Relation_Hard.pth</td>
    <td>51.95</td>
    <td>709</td>
  </tr>
  <tr>
    <td>Logic_Easy.pth</td>
    <td>49.92</td>
    <td>172</td>
  </tr>
  <tr>
    <td>Logic_Medium.pth</td>
    <td>53.27</td>
    <td>376</td>
  </tr>
  <tr>
    <td>Logic_Hard.pth</td>
    <td>61.68</td>
    <td>118</td>
  </tr>
  <tr>
    <td>Ambiguity_Easy.pth</td>
    <td>32.35</td>
    <td>174</td>
  </tr>
  <tr>
    <td>Ambiguity_Medium.pth</td>
    <td>42.62</td>
    <td>1,659</td>
  </tr>
  <tr>
    <td>Ambiguity_Hard.pth</td>
    <td>45.64</td>
    <td>783</td>
  </tr>
  <tr>
    <td>Perspective_Easy.pth</td>
    <td>30.07</td>
    <td>299</td>
  </tr>
  <tr>
    <td>Perspective_Medium.pth</td>
    <td>44.29</td>
    <td>955</td>
  </tr>
  <tr>
    <td>Perspective_Hard.pth</td>
    <td>52.14</td>
    <td>254</td>
  </tr>
  <tr>
    <td>Easy.pth</td>
    <td>33.85</td>
    <td>4,109</td>
  </tr>
  <tr>
    <td>Medium.pth</td>
    <td>46.19</td>
    <td>4,517</td>
  </tr>
  <tr>
    <td>Hard.pth</td>
    <td>47.87</td>
    <td>856</td>
  </tr>
</table>


## Statistics for Difficulty Levels and Referential Types
**STATISTICS OF THE FINE-GRAINED EVALUATION SPLITS ON REFCOCOG-UMD TEST SET. EACH SAMPLE IS ASSIGNED ONE DIFFICULTY LEVEL, WHILE REFERENTIAL CATEGORIES MAY OVERLAP ACROSS SAMPLES.**

<table border="1" style="border-collapse: collapse;">
  <tr>
    <th>Category</th>
    <th>Subset</th>
    <th>Avg. Length</th>
    <th>Samples</th>
    <th>Total</th>
  </tr>
  <tr>
    <td rowspan="3">Difficulty</td>
    <td>Easy</td>
    <td>33.85</td>
    <td>4,109</td>
    <td rowspan="3">9,482</td>
  </tr>
  <tr>
    <td>Medium</td>
    <td>46.19</td>
    <td>4,517</td>
  </tr>
  <tr>
    <td>Hard</td>
    <td>47.87</td>
    <td>856</td>
  </tr>
  <tr>
    <td rowspan="5">Referential Type</td>
    <td>Attribute</td>
    <td>43.33</td>
    <td>7,070</td>
    <td rowspan="5">19,334</td>
  </tr>
  <tr>
    <td>Relation</td>
    <td>44.48</td>
    <td>7,474</td>
  </tr>
  <tr>
    <td>Logic</td>
    <td>53.89</td>
    <td>666</td>
  </tr>
  <tr>
    <td>Ambiguity</td>
    <td>42.84</td>
    <td>2,616</td>
  </tr>
  <tr>
    <td>Perspective</td>
    <td>42.79</td>
    <td>1,508</td>
  </tr>
</table>

## Usage

```python
from huggingface_hub import hf_hub_download
import torch

# Download a specific file
file_path = hf_hub_download(
    repo_id="marloweee/BARE_grefumd_test_partitioning",
    filename="Easy.pth",
    repo_type="dataset"
)

# Load and iterate
data = torch.load(file_path)
for img_name, hw_dict, bbox, phrase, obj_mask in data:
    print(f"Image: {img_name}, Query: {phrase}")
```

## License

This dataset is released under the Apache 2.0 License.