data/README.md

VANTAGE-Bench — data/

Brief overview of the dataset structure and per-task prompts. Ground-truth answers are held server-side; only the question side of each annotation ships here.

Layout

data/
├── 2dbbox/                       # 2D bounding-box detection
│   ├── prompt.json
│   └── <sequence>/images/*.jpg
├── dense_captioning/             # Dense video captioning
│   ├── prompt.json
│   └── *.mp4
├── event_verification/           # Binary event classification
│   └── filtered/
│       ├── metropolis_event_verification/{*.mp4, test_annotation.json}
│       ├── tailgating/{location_a, location_b}/{*.mp4, test_annotation.json}
│       └── warehouse_near_miss/{*.mp4, test_annotations.json}
├── pointing/                     # 2D spatial pointing
│   └── Vantage2DPointing.tsv
├── referring/                    # 2D referring expressions
│   └── refdrone_test_llava.json
├── temporal_localization/        # Temporal grounding
│   ├── *.mp4
│   └── data_jsons/annotations/*.json
├── tracking/                     # Stateless single-object tracking
│   └── sot_benchmark.jsonl
└── vqa/                          # Video question answering
    ├── *.mp4
    └── data_jsons/annotations/*.json

Per-task prompts

Tasks without a per-entry question field carry a top-level prompt.json with the model instruction (schema: {"prompt": "<text>"}).

2dbbox/ — 2D Detection

Locate every instance that belongs to the following categories: person. For each instance of the class, report bbox coordinates in JSON format. Do not group instances and report only individual instances. Avoid reporting duplicate instances.

dense_captioning/ — Dense Video Captioning

Describe the notable events in the provided video. Provide the result in json format with mm:ss.ff format for time depiction for each event. Use keywords start, end and caption in the json output.

vqa/ — Video Question Answering

Per-entry questions in vqa/data_jsons/annotations/*.json. Each entry has {q_uid, question, options, …}; answer keys (gt, gt_option, *_update_*, etc.) are removed.

temporal_localization/ — Temporal Grounding

Per-entry questions in temporal_localization/data_jsons/annotations/*.json. Each entry has {vid, question_id, question, duration, …}; the answer timestamps are removed.

event_verification/ — Binary Event Verification

All four annotation files share a unified schema: {"bcq": [{id, video, system_prompt, question}, …]}. The binary answer is removed.

pointing/ — 2D Spatial Pointing

Vantage2DPointing.tsv — tab-separated. Each row carries the question and multiple-choice options; the last two ground-truth columns are dropped.

referring/ — 2D Referring Expressions

refdrone_test_llava.json — list of LLaVA conversation entries. Only the human turn (the question) is retained; the gpt turn (predicted bboxes) and GT meta fields are removed.

tracking/ — Stateless Single-Object Tracking

sot_benchmark.jsonl — one JSON object per clip with seq_id, scene, camera, init_bbox (the seed bounding box you're given as input), init_frame_id, and canonical_frame_ids (the frames you must predict at). Ground-truth trajectories are held server-side.

Submitting predictions

See the top-level README.md for the eval-server instructions per task.