This work aims to estimate 6Dof (6D) object pose in background clutter. Considering the
strong occlusion and background noise, we propose to utilize the spatial structure for better …

Motivated by various new applications of computational symmetry in computer vision and in
an effort to advance machine perception of symmetry in the wild, we organize the third …

This paper introduces the first minimal solvers that jointly solve for affine-rectification and
radial lens distortion from coplanar repeated patterns. Even with imagery from moderately …

We present an algorithm for producing a seamless animated loop from a single image. The
algorithm detects periodic structures, such as the windows of a building or the steps of a …

We propose an algorithm to detect approximate reflection symmetry present in a set of
volumetrically distributed points belonging to ℝ d containing a distorted reflection symmetry …

We introduce a deep learning approach for grouping discrete patterns common in graphical
designs. Our approach is based on a convolutional neural network architecture that learns a …

This work addresses the challenging problem of reflection symmetry detection in
unconstrained environments. Starting from the understanding on how the visual cortex …

Symmetry is everywhere, found in objects around us, whether artificial or natural, and acts
as a mid-level cue for both human and machine perception of the chaotic real world. From …

In computer vision and graphics, various types of symmetries are extensively studied since
symmetry present in objects is a fundamental cue for understanding the shape and the …

This paper introduces the first minimal solvers that jointly estimate lens distortion and affine
rectification from repetitions of rigidly-transformed coplanar local features. The proposed …