Vision is widely used as a model system to gain insights into how sensory inputs are
processed and interpreted by the brain. Historically, careful quantification and control of …

Inferences made about objects via vision, such as rapid and accurate categorization, are
core to primate cognition despite the algorithmic challenge posed by varying viewpoints and …

High-performing neural networks for vision have dramatically advanced our ability to
account for neural data in biological systems. Recently, further improvement in performance …

Patterns of brain activity contain meaningful information about the perceived world. Recent
decades have welcomed a new era in neural analyses, with computational techniques from …

We hypothesize that high-level visual representations contain more than the representation
of individual categories: they represent complex semantic information inherent in scenes …

With the explosion of visual content on the Internet, creating captions for images has
become a necessary task and an exciting topic for many researchers. Furthermore, image …

The organizational principles of the object space represented in the human ventral visual
cortex are debated. Here we contrast two prominent proposals that, in addition to an …

Human vision is still largely unexplained. Computer vision made impressive progress on this
front, but it is still unclear to which extent artificial neural networks approximate human object …

Understanding how deep neural networks resemble or differ from human vision becomes
increasingly important with their widespread use in Computer Vision and as models in …

To interpret our surroundings, the brain uses a visual categorization process. Current
theories and models suggest that this process comprises a hierarchy of different …