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This is not the latest version of this item. The latest version can be found at: https://fordatis.fraunhofer.de/handle/fordatis/329.3
Full metadata record
DC Field | Value | Language |
---|---|---|
dc.contributor.author | Lehr, Jan | - |
dc.contributor.author | Chavan, Vivek | - |
dc.contributor.author | Koch, Paul | - |
dc.contributor.author | Schlüter, Marian | - |
dc.contributor.author | Briese, Clemens | - |
dc.date.accessioned | 2023-06-19T11:59:32Z | - |
dc.date.available | 2023-06-19T11:59:32Z | - |
dc.date.issued | 2023 | - |
dc.identifier.uri | https://fordatis.fraunhofer.de/handle/fordatis/329 | - |
dc.identifier.uri | http://dx.doi.org/10.24406/fordatis/266 | - |
dc.description.abstract | The Industrial Objects in Varied Contexts (InVar) dataset was internally produced by our team and contains 100 objects in 20800 total images (208 images per class). The objects consist of common automotive, machine and robotics lab parts. Each class contains 4 sub-categories (52 images each) with different attributes and visual complexities. White background (Dwh): The object is against a clean white background and the object is clear, centred and in focus. Stationary Setup (Dst): These images are also taken against a clean background using a stationary camera setup, with uncentered objects at a constant distance. The images have lower DPI resolution with occasional cropping. Handheld (Dha): These images are taken with the user holding the objects, with occasional occluding. Cluttered background (Dcl): These images are taken with the object placed along with other objects from the lab in the background and with no occlusion. The dataset was produced to simulate the miscellaneous issues in industrial setups as discussed. The dataset was produced by our staff at different workstations and labs in Berlin. More details regarding the objects used for digitisation are available in the metadata file. | en |
dc.language.iso | en | en |
dc.rights.uri | https://choosealicense.com/licenses/mit/ | en |
dc.subject | industrial objects | en |
dc.subject | objects in context | en |
dc.subject | fine-grained classification | en |
dc.subject | multimodal dataset | en |
dc.subject | occlusion | en |
dc.subject | clutter | en |
dc.subject.ddc | DDC::600 Technik, Medizin, angewandte Wissenschaften::620 Ingenieurwissenschaften | en |
dc.title | InVar-100: Industrial Objects in Varied Contexts Dataset | en |
dc.type | Image | en |
fordatis.group | Produktion | en |
fordatis.institute | IPK Institut für Produktionsanlagen und Konstruktionstechnik | en |
fordatis.rawdata | false | en |
Appears in Collections: | Institut für Produktionsanlagen und Konstruktionstechnik IPK |
Files in This Item:
File | Description | Size | Format | |
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InVar_100_Class_Metadata.csv | 11,17 kB | CSV | Download/Open | |
image_data.zip Restricted Access | 30,76 GB | ZIP | Download/Open Request a copy | |
InVar-100_Datasheet.pdf | 6,12 MB | Adobe PDF | Download/Open |
Version History
Version | Item | Date | Summary |
---|---|---|---|
3 | fordatis/329.3 | 2024-09-02 13:33:57.346 | The dataset has been slightly altered. Sensitive data in the background (PII, patented devices, etc.) have been removed or blurred. |
2 | fordatis/329.2 | 2023-08-14 11:46:31.857 | The data repository has been updated for the camera-ready submission of the ICCV 2023 paper: Towards Realistic Evaluation of Industrial Continual Learning Scenarios with an Emphasis on Energy Consumption and Computational Footprint. |
1 | fordatis/329 | 2023-06-19 13:59:32.0 | Please use only the updated data under https://fordatis.fraunhofer.de/handle/fordatis/329.2. |
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