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Found 5 papers, 3 papers with code
GePSAn: Generative Procedure Step Anticipation in Cooking Videos
While most previous work focus on the problem of data scarcity in procedural video datasets, another core challenge of future anticipation is how to account for multiple plausible future realizations in natural settings.
Few-shot Learning with Noisy Labels
Our results show that TraNFS is on-par with leading FSL methods on clean support sets, yet outperforms them, by far, in the presence of label noise.
Consistency driven Sequential Transformers Attention Model for Partially Observable Scenes
Most hard attention models initially observe a complete scene to locate and sense informative glimpses, and predict class-label of a scene based on glimpses.
A Probabilistic Hard Attention Model For Sequentially Observed Scenes
A visual hard attention model actively selects and observes a sequence of subregions in an image to make a prediction.
Visual Attention in Imaginative Agents
The next fixation is planned using uncertainty in the content of the imagined scenes.
