Datasets:

UBC-ViL
/

BlackSwanSuite-Gen

configs:
  - config_name: default
    data_files:
      - split: validation
        path: BlackSwanSuite_Gen_Val.jsonl
      - split: test
        path: BlackSwanSuite_Gen_Test.jsonl
task_categories:
  - question-answering
  - summarization
language:
  - en
tags:
  - video
  - video understanding
  - videoqa
license: cc-by-nc-sa-4.0
extra_gated_prompt: >-
  This dataset contains videos from the Oops! Dataset. By selecting the checkbox
  below, and downloading and using this data, you acknowledge that we do not own
  the copyright to these videos and that they are solely provided for
  non-commercial research and/or educational purposes. This dataset is licensed
  under a Creative Commons Attribution-NonCommercial-ShareAlike 4.0
  International License.
extra_gated_fields:
  I agree: checkbox

Black Swan Suite

Black Swan: Abductive and Defeasible Video Reasoning in Unpredictable Events
Aditya Chinchure*, Sahithya Ravi*, Raymond Ng, Vered Shwartz, Boyang Li, Leonid Sigal (* equal)
🎉 Accepted at CVPR 2025
arXiv | Website

Dataset Information

Black Swan has three variants of questions. Please find the data in the appropriate repositories:

This dataset contains questions for Gen (generative) variant the Forecaster, Detective and Reporter tasks in Black Swan.

BlackSwanSuite contains videos of surprising events, split into three parts: the pre-event, the event, and the post-event. In the Generative variant of the tasks:

Forecaster-Gen: Given the pre-event, explain what could happen next in the video.
Detective-Gen: Given the pre-event and the post-event videos, reason about what happened in the main event (hidden part) of the video.
Reporter-Gen: Given the entire video (pre-event, event, post-event), describe the surprising event in the video.

Splits

There are two splits available in this dataset:

Validation: 2381 questions, with ground truth reference sentences
Test: 2484 questions, without ground truth reference sentences (leaderboard submissions will be open soon!)

Cite Us!

@misc{chinchure2024blackswanabductivedefeasible,
      title={Black Swan: Abductive and Defeasible Video Reasoning in Unpredictable Events}, 
      author={Aditya Chinchure and Sahithya Ravi and Raymond Ng and Vered Shwartz and Boyang Li and Leonid Sigal},
      year={2024},
      eprint={2412.05725},
      archivePrefix={arXiv},
      primaryClass={cs.CV},
      url={https://arxiv.org/abs/2412.05725}, 
}