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Found 4 papers, 1 papers with code
Language as the Medium: Multimodal Video Classification through text only
Despite an exciting new wave of multimodal machine learning models, current approaches still struggle to interpret the complex contextual relationships between the different modalities present in videos.
VTC: Improving Video-Text Retrieval with User Comments
In this paper, we a) introduce a new dataset of videos, titles and comments; b) present an attention-based mechanism that allows the model to learn from sometimes irrelevant data such as comments; c) show that by using comments, our method is able to learn better, more contextualised, representations for image, video and audio representations.
Learning Context-Adapted Video-Text Retrieval by Attending to User Comments
Learning strong representations for multi-modal retrieval is an important problem for many applications, such as recommendation and search.
Evaluating Robustness to Context-Sensitive Feature Perturbations of Different Granularities
We cannot guarantee that training datasets are representative of the distribution of inputs that will be encountered during deployment.
