Dataset Card for TaskMeAnything-v1-videoqa-random

TaskMeAnything-v1-videoqa-random dataset

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TaskMeAnything-v1-Random

TaskMeAnything-v1-videoqa-random is a dataset which randomly sampled questions from TaskMeAnything-v1, including 2,700 VideoQA questions. The dataset contains 9 splits, while each splits contains 300 questions from a specific task generator in TaskMeAnything-v1. For each row of dataset, it includes: video, question, options, answer and its corresponding task plan.

Load TaskMeAnything-v1-Random VideoQA Dataset and Convert Video Binary Stream to mp4

• Since Huggingface does not support saving .mp4 files in datasets, we save videos in the format of binary streams. After loading, you can convert the video binary stream to .mp4 using the following method.

import datasets

dataset_name = 'weikaih/TaskMeAnything-v1-videoqa-random'
dataset = datasets.load_dataset(dataset_name, split = TASK_GENERATOR_SPLIT)

# example: convert binary stream in dataset to .mp4 files
video_binary = dataset[0]['video']
with open('/path/save/video.mp4', 'wb') as f:
    f.write(video_binary)

where TASK_GENERATOR_SPLIT is one of the task generators, eg, random_video_3d_what_move.

Evaluation Results

Overall

Breakdown performance on each task types

Out-of-Scope Use

This dataset should not be used for training models.

Disclaimers

TaskMeAnything and its associated resources are provided for research and educational purposes only. The authors and contributors make no warranties regarding the accuracy or reliability of the data and software. Users are responsible for ensuring their use complies with applicable laws and regulations. The project is not liable for any damages or losses resulting from the use of these resources.

Contact

• Jieyu Zhang: jieyuz2@cs.washington.edu

Citation

BibTeX:

@article{zhang2024task,
  title={Task Me Anything},
  author={Zhang, Jieyu and Huang, Weikai and Ma, Zixian and Michel, Oscar and He, Dong and Gupta, Tanmay and Ma, Wei-Chiu and Farhadi, Ali and Kembhavi, Aniruddha and Krishna, Ranjay},
  journal={arXiv preprint arXiv:2406.11775},
  year={2024}
}