Query expansion is a popular method to improve the quality of image retrieval with both
conventional and CNN representations. It has been so far limited to global image similarity …

In this paper we revisit diffusion processes on affinity graphs for capturing the intrinsic
manifold structure defined by pairwise affinity matrices. Such diffusion processes have …

In this paper, we propose an extremely efficient algorithm for visual re-ranking. By
considering the original pairwise distance in the contextual space, we develop a feature …

We propose a novel shape descriptor for matching and recognizing 2D object silhouettes.
The contour of each object is represented by a fixed number of sample points. For each …

Spectral Matching (SM) is a computationally efficient approach to approximate the solution
of pairwise matching problems that are np-hard. In this paper, we present a probabilistic …

In this paper, we propose a new shape/object retrieval algorithm, namely, co-transduction.
The performance of a retrieval system is critically decided by the accuracy of adopted …

This paper presents a new framework for capturing large and complex deformations in
image registration and atlas construction. This challenging and recurrent problem in …

Partial Label Learning (PLL) aims to learn from the data where each training example is
associated with a set of candidate labels, among which only one is correct. The key to deal …

Image retrieval based on deep convolutional features has demonstrated state-of-the-art
performance in popular benchmarks. In this paper, we present a unified solution to address …

In the past few years, the research studies in image-based shape representation have been
proliferating due to its usefulness and importance for various application. This field has been …