8 papers
Understanding Multimodal Complementarity for Single-Frame Action Anticipation
Manuel Benavent-Lledo, Konstantinos Bacharidis, Konstantinos Papoutsakis +2
Human action anticipation is commonly treated as a video understanding problem, implicitly assuming that dense temporal information is required to reason about future actions. In t…
Action Anticipation at a Glimpse: To What Extent Can Multimodal Cues Replace Video?
Manuel Benavent-Lledo, Konstantinos Bacharidis, Victoria Manousaki +3
Anticipating actions before they occur is a core challenge in action understanding research. While conventional methods rely on extracting and aggregating temporal information from…
Enhancing Action Recognition by Leveraging the Hierarchical Structure of Actions and Textual Context
Manuel Benavent-Lledo, David Mulero-Pérez, David Ortiz-Perez +2
We propose a novel approach to improve action recognition by exploiting the hierarchical organization of actions and by incorporating contextualized textual information, including…
CogniAlign: Word-Level Multimodal Speech Alignment with Gated Cross-Attention for Alzheimer's Detection
David Ortiz-Perez, Manuel Benavent-Lledo, Javier Rodriguez-Juan +2
Early detection of cognitive disorders such as Alzheimer's disease is critical for enabling timely clinical intervention and improving patient outcomes. In this work, we introduce…
Deep Insights into Cognitive Decline: A Survey of Leveraging Non-Intrusive Modalities with Deep Learning Techniques
David Ortiz-Perez, Manuel Benavent-Lledo, Jose Garcia-Rodriguez +2
Cognitive decline is a natural part of aging. However, under some circumstances, this decline is more pronounced than expected, typically due to disorders such as Alzheimer's disea…
Text-driven Online Action Detection
Manuel Benavent-Lledo, David Mulero-Pérez, David Ortiz-Perez +1
Detecting actions as they occur is essential for applications like video surveillance, autonomous driving, and human-robot interaction. Known as online action detection, this task…