Datasets:

CyberDancer
/

IBCBench

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 | 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:

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

Then extract the image pool:

unzip IBCBench/images.zip -d IBCBench

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

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

File Structure

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:

{
  "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:

{
  "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:

{photo_id}\t{storage_hash}

Shared Image Pool and Attribution

IBCBench uses the same image pool, metadata, and photo-ID mapping as DISBench, which is derived from the public YFCC100M 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. 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.