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
files (2)
-
295 bytesMD5:
e8ad9f6670d9549be8cdcbd1328ca8a7
README.md -
1,820,195,301 bytesMD5:
40197e7a641f83d15e97267c89173654
Affordance Datasets.zip - download all files (zip)
1,820,195,596 bytes unzipped