1. A method for object instance localization in an image comprising: detecting keypoints in each of a set of labeled reference images, each of the reference images comprising an object instance; describing each of the detected keypoints in the reference images with a local descriptor based on a region of pixels local to the respective keypoint; receiving a target image; detecting keypoints in the target image; describing each of the detected keypoints in the target image with a local descriptor based on a region of pixels local to the respective keypoint; locating candidate regions in the target image, based on matching of keypoints detected in the target image with keypoints detected in the reference images based on their local descriptors; and computing similarity measures between global descriptors computed for the located candidate regions and global descriptors for the reference images; and assigning labels to at least some of the candidate regions based on the computed similarity measures; wherein at least one of the detecting keypoints, locating candidate regions, computing similarity measures, and the assigning of labels is performed with a processor.
1. A method for object instance localization in an image comprising: detecting keypoints in each of a set of labeled reference images, each of the reference images comprising an object instance; describing each of the detected keypoints in the reference images with a local descriptor based on a region of pixels local to the respective keypoint; receiving a target image; detecting keypoints in the target image; describing each of the detected keypoints in the target image with a local descriptor based on a region of pixels local to the respective keypoint; locating candidate regions in the target image, based on matching of keypoints detected in the target image with keypoints detected in the reference images based on their local descriptors; and computing similarity measures between global descriptors computed for the located candidate regions and global descriptors for the reference images; and assigning labels to at least some of the candidate regions based on the computed similarity measures; wherein at least one of the detecting keypoints, locating candidate regions, computing similarity measures, and the assigning of labels is performed with a processor. 6. The method of claim 1 , wherein the global descriptors are fixed length vectors.