--- license: mit task_categories: - question-answering language: - en --- # DISBench: DeepImageSearch Benchmark DISBench is the first benchmark for context-aware image retrieval over visual histories. It contains 122 queries across 57 users and 109,467 photos, requiring multi-step reasoning over corpus-level context. ## Download **Option A: Hugging Face (Recommended)** ```bash huggingface-cli download RUC-NLPIR/DISBench --local-dir DISBench ``` **Option B: Manual Download** ```bash python download_images.py --photo-ids-path photo_ids --images-path images ``` ## File Structure ``` DISBench/ ├── queries.jsonl # 122 annotated queries ├── metadata/ │ └── {user_id}.jsonl # Photo metadata per user ├── images/ │ └── {user_id}/ │ └── {photo_id}.jpg # Photo files ├── photo_ids/ │ └── {user_id}.txt # Photo IDs and hashes per user └── download_images.py # Image download script ``` ## Data Format ### queries.jsonl Each line is a JSON object representing one query: ```json { "query_id": "1", "user_id": "10287726@N02", "query": "Find photos from the musical performance identified by the blue and white event logo on site, where only the lead singer appears on stage.", "answer": ["7759256930", "7759407170", "7759295108", "7759433016"], "event_type": "intra-event" } ``` | Field | Type | Description | |:------|:-----|:------------| | `query_id` | string | Unique query identifier | | `user_id` | string | User whose photo collection to search | | `query` | string | Natural language query (text-only) | | `answer` | list[string] | Ground-truth target photo IDs | | `event_type` | string | `"intra-event"` or `"inter-event"` | ### metadata/{user_id}.jsonl Each line is a JSON object representing one photo's metadata: ```json { "photo_id": "4517621778", "metadata": { "taken_time": "2010-04-10 13:52:57", "longitude": -1.239802, "latitude": 51.754123, "accuracy": 16.0, "address": "Y, Cherwell Street, St Clement's, East Oxford, Oxford, Oxfordshire, England, OX4 1BQ, United Kingdom", "capturedevice": "Panasonic DMC-TZ5" } } ``` | Field | Type | Description | |:------|:-----|:------------| | `photo_id` | string | Unique photo identifier | | `metadata.taken_time` | string | Capture time in `YY-MM-DD HH:MM:SS` format | | `metadata.longitude` | float | GPS longitude. **Missing if unavailable.** | | `metadata.latitude` | float | GPS latitude. **Missing if unavailable.** | | `metadata.accuracy` | float | GPS accuracy level. **Missing if unavailable.** | | `metadata.address` | string | Reverse-geocoded address. **Missing if unavailable.** | | `metadata.capturedevice` | string | Camera/device name. **Missing if unavailable.** | > **Note:** Optional fields (`longitude`, `latitude`, `accuracy`, `address`, `capturedevice`) are omitted entirely when unavailable — they will not appear as keys in the JSON object. ### images/{user_id}/{photo_id}.jpg Photo files organized by user. Each user's collection contains approximately 2,000 photos accumulated chronologically from their photosets. ### photo_ids/{user_id}.txt Each line represents one photo ID and its hash on aws storage in the format `{photo_id}\t{hash}`: ``` 1205732595 c45044fd7b5c9450b2a11adc6b42d ``` | Field | Type | Description | |:------|:-----|:------------| | `photo_id` | string | Unique photo identifier | | `hash` | string | Hashed value of the photo on aws storage | ## Dataset Statistics | Statistic | Value | |:----------|:------| | Total Queries | 122 | | Intra-Event Queries | 57 (46.7%) | | Inter-Event Queries | 65 (53.3%) | | Total Users | 57 | | Total Photos | 109,467 | | Avg. Targets per Query | 3.84 | | Avg. History Span | 3.4 years | | Query Retention Rate | 6.1% (122 / 2,000 candidates) | | Inter-Annotator IoU | 0.91 | ## Data Source DISBench is constructed from [YFCC100M](https://multimediacommons.wordpress.com/yfcc100m-core-dataset/), which preserves a hierarchical structure of users → photosets → photos. All images are publicly shared under Creative Commons licenses. Photoset boundaries are used during construction but are **not** provided to models during evaluation. ## License The DISBench dataset follows the Creative Commons licensing terms of the underlying YFCC100M data. Please refer to individual image licenses for specific usage terms.