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Generative models for active vision
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 …
oculomotor system. While fascinating in its own right, it is also an important model for …
A compositional neural code in high-level visual cortex can explain jumbled word reading
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 …
remain poorly understood. We hypothesized that viewing a jumbled word activates a visual …
Viewpoint dependence and scene context effects generalize to depth rotated three-dimensional objects
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 …
recognition of objects seen from “noncanonical” viewpoints (eg, a cup from below) is …
Do computational models differ systematically from human object perception?
Recent advances in neural networks have revolutionized computer vision, but these
algorithms are still outperformed by humans. Could this performance gap be due to …
algorithms are still outperformed by humans. Could this performance gap be due to …
Invariance of object detection in untrained deep neural networks
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 …
translation, and scaling, is crucial for consistent object recognition. In machine learning …
[HTML][HTML] Human peripheral blur is optimal for object recognition
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 …
periphery. It is widely believed that this high foveal resolution evolved at the expense of …
Humans and deep networks largely agree on which kinds of variation make object recognition harder
SR Kheradpisheh, M Ghodrati… - Frontiers in …, 2016 - frontiersin.org
View-invariant object recognition is a challenging problem that has attracted much attention
among the psychology, neuroscience, and computer vision communities. Humans are …
among the psychology, neuroscience, and computer vision communities. Humans are …
The concurrent encoding of viewpoint-invariant and viewpoint-dependent information in visual object recognition
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 …
paper with Jane Riddoch (1984, p. 385) as “the ability to recognize that an object has the …
Symmetric objects become special in perception because of generic computations in neurons
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 …
phenomena from segmentation to recognition. Yet researchers know little about its neural …
The roles of symmetry and elongation in develo** reference frames
D He, H Ogmen - Frontiers in Psychology, 2024 - frontiersin.org
Previous studies showed that elongation and symmetry (two ubiquitous aspects of natural
stimuli) are important attributes in object perception and recognition, which in turn suggests …
stimuli) are important attributes in object perception and recognition, which in turn suggests …