The MS COCO (Microsoft Common Objects in Context) dataset is a large-scale object detection, segmentation, key-point detection, and captioning dataset. The dataset consists of 328K images.
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The RefCOCO dataset is a referring expression generation (REG) dataset used for tasks related to understanding natural language expressions that refer to specific objects in images. Here are the key details about RefCOCO:
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MobilityAids is a dataset for perception of people and their mobility aids. The annotated dataset contains five classes: pedestrian, person in wheelchair, pedestrian pushing a person in a wheelchair, person using crutches and person using a walking frame. In total the hospital dataset has over 17, 000 annotated RGB-D images, containing people categorized according to the mobility aids they use. The images were collected in the facilities of the Faculty of Engineering of the University of Freiburg and in a hospital in Frankfurt.
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