Computer Vision ePosters

Deep neural networks (DNNs) are extremely vulnerable to adversarial attacks, where small changes to the input, unnoticeable to humans, can drastically alter the model’s predictions. One reason for their poor performance is that they process as much information as possible and make decisions based on the input…

The relationship between vergence and accommodation remains relatively unexplored. The frequent co-occurrence of non-strabismic accommodation and vergence disorders suggests a link between the two processes. Experimental data also reveal that vergence and accommodation have reciprocal effects, where their reflexes…

Much of our current understanding of brain-based visual processing is derived from studies involving immobilised animals. However, in reallife scenarios, visual perception is intrinsically linked with the movements of the eyes, head, and body. To gain amore comprehensive understanding of visual processing under these…

Deep Convolutional Neural Networks (CNNs) are criticised for their reliance on local shape features and texture rather than global shape. We test whether CNNs are able to process global shape information in the absence of local shape cues and texture by testing their performance on Mooney stimuli, which are face…

The human visual cortex processes visual stimuli hierarchically. Early visual areas (V1, V2) of the ventral visual stream feed crude visual features (like orientation and edges) into later visual areas (V4, lateral occipital (Lat Occ), inferior temporal (IT)) that then encode complex visual features (like object…