We demonstrate the need and potential of systematically integrated vision and semantics
solutions for visual sensemaking in the backdrop of autonomous driving. A general …

We demonstrate the need and potential of systematically integrated vision and semantics}
solutions for visual sensemaking (in the backdrop of autonomous driving). A general method …

Driving an automobile involves the tasks of observing surroundings, then making a driving
decision based on these observations (steer, brake, coast, etc.). In autonomous driving, all …

Object perception is a fundamental sub-field of Computer Vision, covering a multitude of
individual areas and having contributed high-impact results. While Machine Learning has …

DLV2 is an AI tool for Knowledge Representation and Reasoning which supports Answer
Set Programming (ASP)–a logic-based declarative formalism, successfully used in both …

The repeated execution of reasoning tasks is desirable in many applicative scenarios, such
as stream reasoning and event processing. When using answer set programming in such …

The architecture described in this paper encodes a theory of intentions based on the key
principles of non-procrastination, persistence, and automatically limiting reasoning to …

Causal and temporal reasoning about video dynamics is a challenging problem. While
neuro-symbolic models that combine symbolic reasoning with neural-based perception and …

We introduce and study a notion of robustness in Qualitative Constraint Networks (QCNs),
which are typically used to represent and reason about abstract spatial and temporal …

Abstract We present ASP Modulo 'Space-Time', a declarative representational and
computational framework to perform commonsense reasoning about regions with both …