<h2>Crêpe Dataset</h2>
<p><img alt="Structured cooking activities" src="https://mfr.osf.io/export?url=https://osf.io/z6yat/?action=download%26direct%26mode=render&initialWidth=565&childId=mfrIframe&format=1200x1200.jpeg"></p>
<h3>Summary</h3>
<p>The Crêpe Dataset provides 6 different types of structured cooking activity videos in 1920x1080 resolution. Each cooking activity is represented as a sequence of different action components. Notable features of this dataset includes:
- Structured activities as a sequence of component actions.
- Multiple activities running in parallel.
- Inclusion of distractors that are not relevant to defined activities.
- Every frame is annotated with bounding boxes, agent types, agent occlusion and action labels.</p>
<p>We provide the following human-labeled annotations:
- Bounding box of every person
- Person type (action performer or distractor)
- Occlusion against another person
- Action label
- Activity label</p>
<p>Here's a sample processed video superimposed with bounding boxes and action recognition likelihoods:
@<a href="https://youtu.be/wqp5JGANh18" rel="nofollow">youtube</a></p>
<h3>Actions</h3>
<ol>
<li>cut</li>
<li>flip</li>
<li>fold</li>
<li>grate</li>
<li>pour</li>
<li>spread</li>
<li>sprinkle</li>
<li>stir</li>
<li>transfer</li>
</ol>
<h3>Activities</h3>
<p>| 1. Lemon and sugar | 2. Nutella and banana with chocholate | 3. Cheese and ham |
|--------------------------------|---------------------------------------|----------------------------------------|
| stir | stir | stir |
| pour | pour | pour |
| spread | spread | spread |
| flip | cut | cut |
| pour | flip | grate |
| | transfer | flip |
| | grate | transfer |
| | fold | fold |
| | | |
| <strong>4. Cheese and ham with parsley</strong> | <strong>5. Goat cheese and spinach</strong> | <strong>6. Goat cheese and spinach with nutmeg</strong> |
| stir | stir | stir |
| pour | pour | pour |
| spread | spread | spread |
| cut | cut | cut |
| grate | flip | flip |
| cut | transfer | transfer |
| flip | fold | sprinkle |
| transfer | | fold |
| sprinkle | | |
| fold | | |</p>
<p>Please see <strong>Annotation</strong> folder for complete information.</p>
<h3>Citation</h3>
<p>If you publish using our data set, we would appreciate if you cite:</p>
<p>K. Lee, D. Ognibene, H. J. Chang, T. K. Kim and Y. Demiris, "STARE: Spatio-Temporal Attention Relocation for Multiple Structured Activities Detection," in IEEE Transactions on Image Processing, vol. 24, no. 12, pp. 5916-5927, Dec. 2015.</p>
<p>For questions and comments, please contact Kyuhwa Lee:
<a href="http://lee.kyuh_at_gmail.com" rel="nofollow">lee.kyuh_at_gmail.com</a></p>
<hr>
<p>The Crêpe dataset creation was funded by EPSRC Network
on Vision and Language, under grant scheme Pump-Priming V&L
Research 2013-1.</p>
