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CORe50

Dataset for Continual Learning and Object Recognition, Detection, Segmentation

CORe50

CORe50, specifically designed for (C)ontinual (O)bject (Re)cognition, is a collection of 50 domestic objects belonging to 10 categories: plug adapters, mobile phones, scissors, light bulbs, cans, glasses, balls, markers, cups and remote controls. Classification can be performed at object level (50 classes) or at category level (10 classes). The first task (the default one) is much more challenging because objects of the same category are very difficult to be distinguished under certain poses.The dataset has been collected in 11 distinct sessions (8 indoor and 3 outdoor) characterized by different backgrounds and lighting. For each session and for each object, a 15 seconds video (at 20 fps) has been recorded with a Kinect 2.0 sensor delivering 300 RGB-D frames.Objects are hand hold by the operator and the camera point-of-view is that of the operator eyes. The operator is required to extend his arm and smoothly move/rotate the object in front of the camera. A subjective point-of-view with objects at grab-distance is well-suited for a number of robotic applications. The grabbing hand (left or right) changes throughout the sessions and relevant object occlusions are often produced by the hand itself.

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University of Bologna
View author website
Task
Object Detection
Annotation Types
Semantic Segmentation
164886
Items
50
Classes
164886
Labels
Models using this dataset
Last updated on 
January 20, 2022
Licensed under 
Research Only
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