A popular approach to pixel labeling problems, such as multiclass image segmentation, is to construct a pairwise conditional Markov random field (CRF) over image pixels where the...
Bottom-up, fully unsupervised segmentation remains a daunting challenge for computer vision. In the cosegmentation context, on the other hand, the availability of multiple images ...
In this paper, we propose a temporal super resolution approach for quasi-periodic image sequence such as human gait. The proposed method effectively combines examplebased and reco...
Naoki Akae, Al Mansur, Yasushi Makihara, Yasushi Y...
We present a method for automatically extracting salient object from a single image, which is cast in an energy minimization framework. Unlike most previous methods that only leve...
Le Wang, IAIR, XJTU, Jianru Xue, Nanning Zheng, Ga...
This paper presents a unified model for image editing in terms of Sparse Matrix-Vector (SpMV) multiplication. In our framework, we cast image editing as a linear energy minimizat...
The use of polygonal meshes for the representation of highly complex geometric objects has become the de facto standard in most computer graphics applications. Especially triangle...
Among the most exciting advances in early vision has been the development of efficient energy minimization algorithms for pixel-labeling tasks such as depth or texture computation....
Richard Szeliski, Ramin Zabih, Daniel Scharstein, ...
We present a general method for matching segmented parts of objects by energy minimization. The energy is designed in order to cope with possible imperfections of the compared segm...
Many tasks in computer vision involve assigning a label (such as disparity) to every pixel. These tasks can be formulated as energy minimization problems. In this paper, we conside...
Reconstructing a 3-D scene from more than one camera is a classical problem in computer vision. One of the major sources of difficulty is the fact that not all scene elements are v...
Vladimir Kolmogorov, Ramin Zabih, Steven J. Gortle...