Weakly supervised discovery of common visual structure in highly variable, cluttered images is a key problem in recognition. We address this problem using deformable part-based mo...
In this paper, we propose a new type of image feature, which consists of patterns of colors and intensities that capture the latent associations among images and primitive feature...
We study the synthesis of neural coding, selective attention and perceptual decision making. We build a hierarchical neural architecture that implements Bayesian integration of no...
In this paper, we propose an image semantic model based on the knowledge and criteria in the field of linguistics and taxonomy. Our work bridges the "semantic gap" by sea...
Xiaoyan Li, Lidan Shou, Gang Chen, Tianlei Hu, Jin...
This paper presents a novel algorithm for computing the relative motion between images from compressed linear measurements. We propose a geometry based correlation model that desc...