PASCAL VOC 2012 (VOC2012) is a standard benchmark dataset from the PASCAL Visual Object Classes (VOC) challenge series for object recognition tasks including image classification, object detection, and pixel-level semantic segmentation. The VOC2012 release provides images collected from Flickr with high-quality annotations: bounding boxes and class labels for objects, and pixel-wise segmentation masks for a subset of images. It covers 20 common object classes plus background and has been widely used as a semantic segmentation benchmark (and for detection/classification). The commonly-cited VOC2012 train/val collection contains 11,530 images (with ~27,450 ROI-tagged objects and ~6,929 segmentation annotations in the release), and the dataset is distributed together with devkit/evaluation code and documentation. Note that many images originate from Flickr and must be used in accordance with their license/terms.
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