Retail Objects Affordance Dataset, underlying the MSc thesis: Object Affordance Detection for Mobile Manipulation in Retail Environments
doi:10.4121/14557965.v1
The doi above is for this specific version of this dataset, which is currently the latest. Newer versions may be published in the future.
For a link that will always point to the latest version, please use
doi: 10.4121/14557965
doi: 10.4121/14557965
Datacite citation style:
van Houtum, Paul (2021): Retail Objects Affordance Dataset, underlying the MSc thesis: Object Affordance Detection for Mobile Manipulation in Retail Environments. Version 1. 4TU.ResearchData. dataset. https://doi.org/10.4121/14557965.v1
Other citation styles (APA, Harvard, MLA, Vancouver, Chicago, IEEE) available at Datacite
Dataset
Synthetically generated affordance dataset consisting of 3237 images with pixel-level annotations for either graspable or pushable affordance classes. Further, 204 annotated real images of similar scenarios are included.Images contain retail store related objects lying of supermarket floors, together with a semantic masks differentiating the object from the background.
history
- 2021-05-11 first online, published, posted
publisher
4TU.ResearchData
format
Images:
.png .jpg
mask + label: .
Synthetic data -> .png + .txt
Real image data -> .jpg + .json
organizations
TU Delft, Faculty of Mechanical, Maritime and Materials Engineering, Department of Cognitive Robotics.
DATA
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- 295 bytesMD5:
e8ad9f6670d9549be8cdcbd1328ca8a7
README.md - 1,820,195,301 bytesMD5:
40197e7a641f83d15e97267c89173654
Affordance Datasets.zip -
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