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Action Forecasting with Feature-wise Self-Attention
A temporal recurrent encoder captures temporal information of input videos while a self-attention model is used to attend on relevant feature dimensions of the input space.
Forecasting future action sequences with attention: a new approach to weakly supervised action forecasting
We extend our action sequence forecasting model to perform weakly supervised action forecasting on two challenging datasets, the Breakfast and the 50Salads.
Commonsense inference in human-robot communication
Natural language communication between machines and humans are still constrained.
Human Action Sequence Classification
Furthermore, we use our model that is trained to output action sequences to solve downstream tasks; such as video captioning and action localization.
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