The core of multiple-view geometry is governed by the fundamental matrix and the trilinear tensor. In this paper we unify both representations by rst deriving the fundamental matrix as a rank-2 trivalent tensor, and secondly by deriving a uniied set of operators that are transparent to the number of views. As a result, we show that the basic building block of the geometry of multiple views is a...

This paper presented a view interpolation method for reconstructing intermediate all-in-focus images between defocused stereo images of a scene consisting of two depths. In the presented method, the novel view can be reconstructed as a sum of the filtered stereo images. The reconstruction filter was derived as a stable and linear space-invariant one; thus the presented method does not require r...

In this paper, we present an algorithm for multi-view recognition in a distributed camera setting that learns which viewpoints are most discriminative for particular instances of ambiguity. Our method is built on top of 2D recognition algorithms and casts view selection as the problem of optimizing kernel weights in multiple kernel learning. The main contribution is a locality-sensitive meta-tr...

The development of high-dimensional generative models has recently gained a great surge of interest with the introduction of variational auto-encoders and generative adversarial neural networks. Different variants have been proposed where the underlying latent space is structured, for example, based on attributes describing the data to generate. We focus on a particular problem where one aims a...

Multi-view learning improves the performance of existing tasks by using complementary information between multiple feature sets. In latest research, multi-view model privileged is proposed; specific models are PSVM-2V and MCPK. these models, views complement each other acting as policies; however, a single view contains that can guide classifier, framework does not consider it. order to use thi...