Abstract. We propose a novel Multiple Instance Learning (MIL) framework to perform target localization from image sequences. The proposed approach consists of a softmax logistic re...
We address a novel problem domain in the analysis of optical coherence tomography (OCT) images: the diagnosis of multiple macular pathologies in retinal OCT images. The goal is to ...
Yu-Ying Liu, Mei Chen, Hiroshi Ishikawa 0002, Gadi...
We propose a framework for compressive sensing of images with local geometric features. Specifically, let x ∈ RN be an N-pixel image, where each pixel p has value xp. The image...
Rishi Gupta, Piotr Indyk, Eric Price, Yaron Rachli...
We propose a novel and robust model to represent and learn generic 3D object categories. We aim to solve the problem of true 3D object categorization for handling arbitrary rotati...
Tracking multiple interacting objects represents a challenging area in computer vision. The tracking problem in general can be formulated as the task of recovering the spatio-temp...