3 accepted papers
Video recognition models are typically trained on fixed taxonomies which are often too coarse, collapsing distinctions in object, manner or outcome under a single label. As tasks and definitions evolve, such models cannot accommodate emerging distinctions and collecting new annotations and retrainin…
We present a validation dataset of newly-collected kitchen based egocentric videos, manually annotated with highly detailed and interconnected ground-truth labels covering: recipe steps, fine-grained actions, ingredients with nutritional values, moving objects, and audio annotations. Importantly, al…
Feature selection algorithms aim to select a subset of informative features from a dataset to reduce the data dimensionality, consequently saving resource consumption and improving the model’s performance and interpretability. In recent years, feature selection based on neural networks has become a…