The active visual system comprises the visual cortices, cerebral attention networks, and
oculomotor system. While fascinating in its own right, it is also an important model for …

We read jubmled wrods effortlessly, but the neural correlates of this remarkable ability
remain poorly understood. We hypothesized that viewing a jumbled word activates a visual …

Recent advances in neural networks have revolutionized computer vision, but these
algorithms are still outperformed by humans. Could this performance gap be due to …

The ability to perceive visual objects with various types of transformations, such as rotation,
translation, and scaling, is crucial for consistent object recognition. In machine learning …

Our vision is sharpest at the centre of our gaze and becomes progressively blurry into the
periphery. It is widely believed that this high foveal resolution evolved at the expense of …

View-invariant object recognition is a challenging problem that has attracted much attention
among the psychology, neuroscience, and computer vision communities. Humans are …

Viewpoint effects on object recognition interact with object-scene consistency effects. While
recognition of objects seen from “noncanonical” viewpoints (eg, a cup from below) is …

ABSTRACT A major theme of Glyn Humphreys' career was object constancy, defined in his
paper with Jane Riddoch (1984, p. 385) as “the ability to recognize that an object has the …

Symmetry is a salient visual property: It is easy to detect and influences perceptual
phenomena from segmentation to recognition. Yet researchers know little about its neural …

Object recognition is challenging because the same object can produce vastly different
images, mixing signals related to its identity with signals due to its image attributes, such as …