TACoS Corpus Download

License

By downloading the TACoS corpus, you agree to our terms of use in our License Agreement. Basically, this agreement states that you are free to use the corpus for research or educational purposes, and asks you to cite this paper if you do so:

Michaela Regneri, Marcus Rohrbach, Dominikus Wetzel, Stefan Thater, Bernt Schiele and Manfred Pinkal (2013):
Grounding Action Descriptions in Videos.
In Transactions of the Association for Computational Linguistics (TACL), Vol. 1. [PDF]

Bibtex:

@article{tacos:regnerietal:tacl,
   Author = {Regneri, Michaela and Rohrbach, Marcus and 
             Wetzel, Dominikus and Thater, Stefan and 
             Schiele, Bernt and Pinkal, Manfred}, 
   Journal = {Transactions of the Association for Computational 
              Linguistics (TACL)},
   Title = {Grounding Action Descriptions in Videos},
   Year = {2013},
   Volume = {1},
   Pages = {25-36}}
   

Corpus

The TACoS Corpus consists of 127 videos of basic kitchen tasks, low-level activity and object annotation for those videos and timed natural language sentences that describe what happens in the video. We provide:

Content	Download
All of the textual data in one archive	[zip file, 2.4 mb]
The set of videos, hosted at MPI for Informatics	[zip file, 11 gb]
The list of kitchen tasks, mapped to the videos we have for this task	[tsv]
The list of all sentences we collected, annotated with the videos and the timeframes of the actions they describe	[all in one, 1.5mb] [Split into videos]
For each video, an alignment table with time frames, low-level annotation and natural language sentences	[zip file]
For each video, the same alignment but human readable (with plain text instead of sentence ids)	[zip file]
The annotation guidelines we published on Mechanical turk	[HTML]
ASim: A list of 900 action description pairs, annotated with action similarities by 3 native speakers	[tsv]
The README describing the file contents and formats	[text]
The raw visual features for the videos	[Matlab file, 41 mb]
The feature output of the visual classifier used in the paper	[Matlab file]
The License Agreement	[HTML] [text]