User profiles for Christina M. Funke
 | Christina Maria FunkeUniversity of Tübingen Verified email at bethgelab.org Cited by 255 |
[HTML][HTML] Five points to check when comparing visual perception in humans and machines
With the rise of machines to human-level performance in complex recognition tasks, a
growing amount of work is directed toward comparing information processing in humans and …
growing amount of work is directed toward comparing information processing in humans and …
[HTML][HTML] A parametric texture model based on deep convolutional features closely matches texture appearance for humans
Our visual environment is full of texture—“stuff” like cloth, bark, or gravel as distinct from “things”
like dresses, trees, or paths—and humans are adept at perceiving subtle variations in …
like dresses, trees, or paths—and humans are adept at perceiving subtle variations in …
Image content is more important than Bouma's Law for scene metamers
10.7554/eLife.42512.001 We subjectively perceive our visual field with high fidelity, yet
peripheral distortions can go unnoticed and peripheral objects can be difficult to identify (…
peripheral distortions can go unnoticed and peripheral objects can be difficult to identify (…
[PDF][PDF] The notorious difficulty of comparing human and machine perception
With the rise of machines to human-level performance in complex recognition tasks, a
growing amount of work is directed towards comparing information processing in humans and …
growing amount of work is directed towards comparing information processing in humans and …
Disentanglement and generalization under correlation shifts
Correlations between factors of variation are prevalent in real-world data. Exploiting such
correlations may increase predictive performance on noisy data; however, often correlations …
correlations may increase predictive performance on noisy data; however, often correlations …
Synthesising dynamic textures using convolutional neural networks
Here we present a parametric model for dynamic textures. The model is based on
spatiotemporal summary statistics computed from the feature representations of a Convolutional …
spatiotemporal summary statistics computed from the feature representations of a Convolutional …
[PDF][PDF] 2.1 Synthesis of Dynamic Textures (P1)
Results We developed a model that captures second-order dependencies between spatial
features. Our model was similar to the static DNN texture model (Gatys et al., 2015), but …
features. Our model was similar to the static DNN texture model (Gatys et al., 2015), but …
Hole-in-the-wall: Perception of 3D shape and affordances from static images in humans and machines
One popular toy for toddlers involves sorting block shapes into their respective holes. While
toddlers require trial-and-error actions to sort blocks correctly, adults can rapidly see the …
toddlers require trial-and-error actions to sort blocks correctly, adults can rapidly see the …
Towards matching the peripheral visual appearance of arbitrary scenes using deep convolutional neural networks
Distortions of image structure can go unnoticed in the visual periphery, and objects can be
harder to identify (crowding). Is it possible to create equivalence classes of images that …
harder to identify (crowding). Is it possible to create equivalence classes of images that …
[PDF][PDF] A parametric texture model
TSA Wallis, CM Funke, AS Ecker… - … in Biological and …, 2017 - tobias-lib.ub.uni-tuebingen.de
Textures are characterized by the repetition of smaller elements, sometimes with variation,
to make up a pattern. Significant portions of the visual environment can be thought of as …
to make up a pattern. Significant portions of the visual environment can be thought of as …