Datasets:

Modalities:
Text
Video
Formats:
csv
ArXiv:
Libraries:
Datasets
pandas
License:
Vinoground / README.md
harris
add readme for lmms-eval
b2aef31
metadata
license: apache-2.0
dataset_info:
  config_name: default
  features:
    - name: index
      dtype: string
    - name: major
      dtype: string
    - name: minor
      dtype: string
    - name: pos_vid
      dtype: string
    - name: pos_start
      dtype: string
    - name: pos_end
      dtype: string
    - name: pos_cap
      dtype: string
    - name: neg_vid
      dtype: string
    - name: neg_start
      dtype: string
    - name: neg_end
      dtype: string
    - name: neg_cap
      dtype: string
configs:
  - config_name: default
    data_files:
      - split: test
        path: vinoground.csv
      - split: lmmseval
        path: vinoground_lmmseval.csv
extra_gated_prompt: >-
  Vinoground is made for academic research purposes only. Commercial use in any
  form is strictly prohibited.

  The copyright of all videos belong to their respective owners. We do not own
  any of the videos.

  Any form of unauthorized distribution, publication, copying, dissemination, or
  modifications made over Vinoground in part or in whole is strictly prohibited.

  You cannot access our dataset unless you comply to all the above restrictions
  and also provide your information for legal purposes.
extra_gated_fields:
  Name: text
  Country: country
  Affiliation: text
  Job title:
    type: select
    options:
      - Undergraduate Student
      - Graduate Student
      - AI researcher/developer/engineer
      - Other
  By clicking Submit below I accept the terms and conditions and acknowledge that the information I provide is only for legal purposes and will not be shared with any other entity: checkbox
extra_gated_button_content: Submit

This repository holds the dataset Vinoground, a temporal counterfactual dataset composed of 1000 short and natural video-caption pairs.This benchmark has also been integrated into [lmms-eval] and will be announced in their next public release. One can begin using it by cloning their repository. Evaluation is now made easier. You can also use the evaluation codes we provided in this repository.

Project page: https://vinoground.github.io

Paper: https://arxiv.org/abs/2410.02763

Code: https://github.com/Vinoground/Vinoground

Leaderboard: https://paperswithcode.com/sota/temporal-relation-extraction-on-vinoground