The PASCAL Visual Object Classes (VOC) 2012 dataset contains 20 object categories including vehicles, household, animals, and other: aeroplane, bicycle, boat, bus, car, motorbike, train, bottle, chair, dining table, potted plant, sofa, TV/monitor, bird, cat, cow, dog, horse, sheep, and person. Each image in this dataset has pixel-level segmentation annotations, bounding box annotations, and object class annotations. This dataset has been widely used as a benchmark for object detection, semantic segmentation, and classification tasks. The PASCAL VOC dataset is split into three subsets: 1,464 images for training, 1,449 images for validation and a private testing set.
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Occluded REID is an occluded person dataset captured by mobile cameras, consisting of 2,000 images of 200 occluded persons (see Fig. (c)). Each identity has 5 full-body person images and 5 occluded person images with different types of occlusion.
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SPair-71k contains 70,958 image pairs with diverse variations in viewpoint and scale. Compared to previous datasets, it is significantly larger in number and contains more accurate and richer annotations.
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The BirdSong dataset consists of audio recordings of bird songs at the H. J. Andrews (HJA) Experimental Forest, using unattended microphones. The goal of the dataset is to provide data to automatically identify the species of bird responsible for each utterance in these recordings. The dataset contains 548 10-seconds audio recordings.
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The LINUX dataset consists of 48,747 Program Dependence Graphs (PDG) generated from the Linux kernel. Each graph represents a function, where a node represents one statement and an edge represents the dependency between the two statements
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Mindboggle is a large publicly available dataset of manually labeled brain MRI. It consists of 101 subjects collected from different sites, with cortical meshes varying from 102K to 185K vertices. Each brain surface contains 25 or 31 manually labeled parcels.
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The DispScenes dataset was created to address the specific problem of disparate image matching. The image pairs in all the datasets exhibit high levels of variation in illumination and viewpoint and also contain instances of occlusion. The DispScenes dataset provides manual ground truth keypoint correspondences for all images.
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