Motion coherence is an important clue for distinguishing true correspondences from false
ones. Modeling motion coherence on sparse putative correspondences is challenging due …

Subspace clustering has been extensively studied from the hypothesis-and-test, algebraic,
and spectral clustering-based perspectives. Most assume that only a single type/class of …

In this paper, a new robust model fitting method is proposed to efficiently segment
multistructure data even when they are heavily contaminated by outliers. The proposed …

Robust model fitting is an important task for modern electronic industries. In this paper, an
efficient robust model-fitting method is proposed to estimate model hypotheses for …

In this article, we propose a novel hierarchical representation via message propagation
(HRMP) method for robust model fitting, which simultaneously takes advantages of both the …

We address the problem of segmenting moving rigid objects based on two-view image
correspondences under a perspective camera model. While this is a well understood …

With the emergence of Vision Transformers, attention-based modules have demonstrated
comparable or superior performance in comparison to CNNs on various vision tasks …

Finding robust and accurate feature matches is a fundamental problem in computer vision.
However, incorrect correspondences and suboptimal matching accuracies lead to significant …

As the demand for data-driven techniques in machine learning and computer vision
continues to rise, the reliance on unsupervised learning methods becomes increasingly …

Abstract Deep Neural Networks (DNNs) are often criticized for being susceptible to
adversarial attacks. Most successful defense strategies adopt adversarial training or random …