More than one hundred benchmarks have been developed to test the commonsense
knowledge and commonsense reasoning abilities of artificial intelligence (AI) systems …

Human visual perception carves a scene at its physical joints, decomposing the world into
objects, which are selectively attended, tracked and predicted as we engage our …

What makes a video task uniquely suited for videos, beyond what can be understood from a
single image? Building on recent progress in self-supervised image-language models, we …

The visual world can be parsimoniously characterized in terms of distinct entities with sparse
interactions. Discovering this compositional structure in dynamic visual scenes has proven …

Abstract 'Intuitive physics' enables our pragmatic engagement with the physical world and
forms a key component of 'common sense'aspects of thought. Current artificial intelligence …

Abstract We propose Anticipative Video Transformer (AVT), an end-to-end attention-based
video modeling architecture that attends to the previously observed video in order to …

Object-centric representations are a promising path toward more systematic generalization
by providing flexible abstractions upon which compositional world models can be built …

Unsupervised object-centric learning aims to represent the modular, compositional, and
causal structure of a scene as a set of object representations and thereby promises to …

Recently, tracking-by-detection has become a popular paradigm in Multiple-object tracking
(MOT) for its concise pipeline. Many current works first associate the detections to form track …

Reasoning in the real world is not divorced from situations. How to capture the present
knowledge from surrounding situations and perform reasoning accordingly is crucial and …