Learning visual classifiers for object recognition from weakly labeled data requires determining correspondence between image regions and semantic object classes. Most approaches u...
Abstract. We present a comparative study on how to use discriminative learning methods such as classification, regression, and ranking to address deformable shape segmentation. Tra...
Jingdan Zhang, Shaohua Kevin Zhou, Dorin Comaniciu...
The Random Sample Consensus (RANSAC) algorithm is a popular tool for robust estimation problems in computer vision, primarily due to its ability to tolerate a tremendous fraction o...
Abstract. Deformable models are by their formulation able to solve surface extraction problem from noisy volumetric images. This is since they use image independent information, in...
A richer set of land-cover classes are observable in satellite imagery than ever before due to the increased sub-meter resolution. Individual objects, such as cars and houses, are...