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DiffAnt: Diffusion Models for Action Anticipation
However, the majority of existing action anticipation models adhere to a deterministic approach, neglecting to account for future uncertainties.
A Survey on Deep Learning Techniques for Action Anticipation
The ability to anticipate possible future human actions is essential for a wide range of applications, including autonomous driving and human-robot interaction.
Drive&Act: A Multi-Modal Dataset for Fine-Grained Driver Behavior Recognition in Autonomous Vehicles
We introduce the novel domain-specific Drive&Act benchmark for fine-grained categorization of driver behavior.
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