Within months of birth, children develop meaningful expectations about the world around
them. How much of this early knowledge can be explained through generic learning …

Infants possess a remarkable ability to rapidly learn and process visual inputs. As an infant's
mobility increases, so does the variety and dynamics of their visual inputs. Is this change in …

Since the time of Turing, computer scientists have dreamed of building artificial general
intelligence (AGI)-a system that can think, learn and act as humans do. Over recent years …

Video self-supervised learning (VSSL) has made significant progress in recent years.
However, the exact behavior and dynamics of these models under different forms of …

Deep neural networks are popular for visual perception tasks such as image classification
and object detection. Once trained and deployed in a real-time environment, these models …

Biological vision systems are unparalleled in their ability to learn visual representations
without supervision. In machine learning, self-supervised learning (SSL) has led to major …

Research in child development has shown that embodied experience handling physical
objects contributes to many cognitive abilities, including visual learning. One characteristic …

Infants see a selective view of the world: they see some objects with high frequency and
from a wide range of viewpoints (eg, their toys during playing) while a much larger set of …

Deep neural networks have recently become remarkable computational tools for thinking
about human visual learning. Recent studies have explored the effects of altering naturalistic …

We add one more invariance-state invariance-to the more commonly used other invariances
for learning object representations for recognition and retrieval. By state invariance, we …