With the rapid development and popularity of the Internet, multimedia security has become a
general essential concern. Especially, as manipulation of digital images gets much easier …

Convolutional neural networks (CNNs) were inspired by early findings in the study of
biological vision. They have since become successful tools in computer vision and state-of …

Convolutional architectures have proven extremely successful for vision tasks. Their hard
inductive biases enable sample-efficient learning, but come at the cost of a potentially lower …

Artificial neural networks suffer from catastrophic forgetting. Unlike humans, when these
networks are trained on something new, they rapidly forget what was learned before. In the …

Assembly101 is a new procedural activity dataset featuring 4321 videos of people
assembling and disassembling 101" take-apart" toy vehicles. Participants work without fixed …

Abstract The goal of No-Reference Image Quality Assessment (NR-IQA) is to estimate the
perceptual image quality in accordance with subjective evaluations, it is a complex and …

Convolutions are a fundamental building block of modern computer vision systems. Recent
approaches have argued for going beyond convolutions in order to capture long-range …

The collective activity of a population of neurons, beyond the properties of individual cells, is
crucial for many brain functions. A fundamental question is how activity correlations between …

Neuroscience research is undergoing a minor revolution. Recent advances in machine
learning and artificial intelligence research have opened up new ways of thinking about …

Batch Normalization (BN) is a milestone technique in the development of deep learning,
enabling various networks to train. However, normalizing along the batch dimension …