Recent progress in deep learning is essentially based on a “big data for small tasks”
paradigm, under which massive amounts of data are used to train a classifier for a single …

To what extent do modern AI systems comprehend the physical world? We introduce the
open-access Infant-Level Physical Reasoning Benchmark (InfLevel) to gain insight into this …

Intuitive physics is pivotal for human understanding of the physical world, enabling
prediction and interpretation of events even in infancy. Nonetheless, replicating this level of …

Object Permanence allows people to reason about the location of non-visible objects, by
understanding that they continue to exist even when not perceived directly. Object …

Aiming to understand how human (false-) belief—a core socio-cognitive ability—would affect
human interactions with robots, this paper proposes to adopt a graphical model to unify the …

Open containers, ie, containers without covers, are an important and ubiquitous class of
objects in human life. In this letter, we propose a novel method for robots to “imagine” the …

Creating dynamic virtual environments consisting of humans interacting with objects is a
fundamental problem in computer graphics. While it is well‐accepted that agent interactions …

The functionality of a workspace is one of the most important considerations in both virtual
world design and interior design. To offer appropriate functionality to the user, designers …

Acquiring knowledge about object interactions and affordances can facilitate scene
understanding and human-robot collaboration tasks. As humans tend to use objects in many …

This paper provides a review on representation learning for videos. We classify recent spatio-
temporal feature learning methods for sequential visual data and compare their pros and …