In this paper, we propose a novel approach to model shape variations. It encodes sparsity, exploits geometric redundancy, and accounts for the different degrees of local variation...
In this paper, we proposed a neural network based scheme for performing unsupervised video object segmentation, especially for videophone or videoconferencing applications. The pr...
Anastasios D. Doulamis, Nikolaos D. Doulamis, Stef...
We address the problem of computing joint sparse representation of visual signal across multiple kernel-based representations. Such a problem arises naturally in supervised visual...
Due to the lack of explicit spatial consideration, existing
epitome model may fail for image recognition and target detection,
which directly motivates us to propose the so-calle...
Xinqi Chu, Shuicheng Yan, Liyuan Li, Kap Luk Chan,...
Decoding is a strategy that allows us to assess the amount of information neurons can provide about certain aspects of the visual scene. In this study, we develop a method based o...