README.md

---
pretty_name: IBCBench
language:
- en
license: other
task_categories:
- other
tags:
- image-retrieval
- multi-image-retrieval
- multimodal-agents
- image-bundle-composition
- visual-history
- yfcc100m
configs:
- config_name: default
  data_files:
  - split: test
    path: queries.jsonl
---

# IBCBench: Image Bundle Composition Benchmark

IBCBench is the benchmark introduced in **Weaving Visual Narratives: Agentic Image Bundle Composition Beyond Atomic Visual Matching**, accepted to the **EMNLP 2026 Main Conference**.

[**GitHub**](https://github.com/LaVieEnRose365/Image-Bundle-Composition) | **Paper link coming soon**

## Overview

Image Bundle Composition (IBC) shifts image retrieval from independently ranking images to dynamically composing a compact, cohesive bundle whose images jointly satisfy relational, temporal, spatial, or narrative constraints. The target bundles are not predefined in the image pool, so systems must reason over non-decomposable bundle-level relevance in a combinatorial search space.

IBCBench contains **667 human-verified queries** evaluated against a pool of **109,467 images from 57 users**. Each ground-truth bundle contains 3--5 images. The benchmark was built using a semi-automated candidate mining and verification pipeline followed by expert human review.

## Dataset Statistics

| Statistic | Value |
|:--|--:|
| Queries | 667 |
| Images | 109,467 |
| Users | 57 |
| Bundle size: 3 images | 162 (24.3%) |
| Bundle size: 4 images | 215 (32.2%) |
| Bundle size: 5 images | 290 (43.5%) |
| Same-location dynamics | 52.5% |
| Cross-location structures | 47.5% |

## Download

Download the complete benchmark from the Hugging Face Hub:

```bash
hf download CyberDancer/IBCBench --repo-type dataset --local-dir IBCBench
```

Then extract the image pool:

```bash
unzip IBCBench/images.zip -d IBCBench
```

Alternatively, the included `download_images.py` script can reconstruct the image pool from `photo_ids/`:

```bash
python IBCBench/download_images.py \
  --photo-ids-path IBCBench/photo_ids \
  --images-path IBCBench/images
```

## File Structure

```text
IBCBench/
├── queries.jsonl              # 667 IBC queries and ground-truth bundles
├── metadata/
│   └── {user_id}.jsonl        # Photo metadata for each user
├── photo_ids/
│   └── {user_id}.txt          # Photo IDs and storage hashes for each user
├── images.zip                # images/{user_id}/{photo_id}.jpg
└── download_images.py        # Alternative image downloader
```

## Query Format

Each line in `queries.jsonl` is one query and its ground-truth image bundle:

```json
{
  "query_id": "10287726@N02_s18_w0_n3",
  "query": "Find a bundle documenting the same spectator's Olympic viewing experience: ...",
  "image_ids": ["7797992908", "7797994344", "7797998284"]
}
```

| Field | Type | Description |
|:--|:--|:--|
| `query_id` | string | Unique query identifier. Its prefix is the YFCC user ID. |
| `query` | string | Natural-language bundle query in English. |
| `image_ids` | list[string] | Ground-truth set of 3--5 YFCC photo IDs. |

## Photo Metadata Format

Each line in `metadata/{user_id}.jsonl` describes one image:

```json
{
  "photo_id": "4517621778",
  "metadata": {
    "taken_time": "2010-04-10 13:52:57",
    "longitude": -1.239802,
    "latitude": 51.754123,
    "accuracy": 16.0,
    "address": "...",
    "capturedevice": "Panasonic DMC-TZ5"
  }
}
```

The location, address, accuracy, and capture-device fields are optional and may be absent. Album identifiers are intentionally excluded from the benchmark.

Each non-empty line in `photo_ids/{user_id}.txt` has the following tab-separated form:

```text
{photo_id}\t{storage_hash}
```

## Shared Image Pool and Attribution

IBCBench uses the same image pool, metadata, and photo-ID mapping as [DISBench](https://huggingface.co/datasets/RUC-NLPIR/DISBench), which is derived from the public [YFCC100M](https://multimediacommons.wordpress.com/yfcc100m-core-dataset/) collection. IBCBench contributes a separate set of 667 queries and ground-truth bundles for the Image Bundle Composition task.


## Ethical Considerations

The source images were publicly distributed under Creative Commons licenses. IBCBench is intended for research on multimodal retrieval and relational reasoning, particularly user-centric organization of personal photo collections. It is not intended for unauthorized surveillance, identity profiling, or analysis of private third-party collections.

Although the source media is public, the benchmark includes spatiotemporal metadata. Users should handle this information responsibly and follow the terms attached to each original image.

## License

The IBCBench query annotations and BundleWeaver project are released under the [Apache License 2.0](https://github.com/LaVieEnRose365/Image-Bundle-Composition/blob/main/LICENSE). The images retain the individual Creative Commons licenses attached to the corresponding YFCC100M records; downstream users are responsible for checking and following those terms. The included DISBench-derived helper and shared files retain their upstream terms.