---
dataset_info:
  features:
  - name: image
    dtype: image
  - name: question_id
    dtype: string
  - name: question
    dtype: string
  - name: answer
    dtype: string
  - name: source
    dtype: string
  - name: eval_type
    dtype: string
  - name: relation_type
    dtype: string
  configs:
  - config_name: default
    data_files:
    - split: train
      path: data-*.parquet
license: cc-by-4.0
task_categories:
- visual-question-answering
language:
- en
tags:
- visual-relation
- spatial-relation
- action-relation
- comparative-relation
- dall-e
size_categories:
- 1K<n<10K
---

# MMRel

Multimodal visual relation benchmark with 3,613 Dall-E generated image-question pairs testing action, spatial, and comparative relations. Each image is synthesized in multiple artistic styles (photo-realistic, watercolor, abstract, oil painting).

Note: The full MMRel benchmark also includes Visual Genome and SPEC (SDXL) images, which require separate download from their respective sources.

## Fields

| Field | Description |
|-------|-------------|
| image | Dall-E synthesized image |
| question_id | Unique question identifier |
| question | Relation question (yes/no or open-ended) |
| answer | Ground truth answer |
| source | Image source (dall-e) |
| eval_type | discriminative / generative |
| relation_type | dall-e_action / dall-e_spatial |

## Evaluation

```
Discriminative: "Does {relation} exist? Please answer with one word."
  metrics: Accuracy, Precision, Recall, F1
  parser: yes/no binary

Generative: "What is the {relation_type} between {obj1} and {obj2}?"
  metrics: Relation extraction accuracy
  parser: free-text matching
```

## Source

Original data from [MMRel](https://huggingface.co/datasets/Jingkang50/MMRel) (arXiv 2024).