Data Augmentation Techniques for the Video Question Answering Task

Falcon, Alex; Lanz, Oswald; Serra, Giuseppe

doi:10.1007/978-3-030-66415-2_33

Computer Vision – ECCV 2020 Workshops

2020

DOI: 10.1007/978-3-030-66415-2_33

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Data Augmentation Techniques for the Video Question Answering Task

Alex Falcon

Oswald Lanz

Giuseppe Serra

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2021

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“…Propose a DA method for emotion recognition from a combination of audio, visual, and textual modalities Mou et al (2020). Introduce a DA method for Audio-Video Scene-Aware Dialogue, which involves dialogue containing a sequence of QA pairs about a video Falcon et al (2020). Investigate DA techniques for video QA including mirroring and horizontal flipping.…”

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confidence: 99%

A Survey of Data Augmentation Approaches for NLP

Feng

Gangal

Wei

et al. 2021

Findings of the Association for Computational Linguistics: ACL-IJCNLP 2021

296

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Data augmentation has recently seen increased interest in NLP due to more work in lowresource domains, new tasks, and the popularity of large-scale neural networks that require large amounts of training data. Despite this recent upsurge, this area is still relatively underexplored, perhaps due to the challenges posed by the discrete nature of language data. In this paper, we present a comprehensive and unifying survey of data augmentation for NLP by summarizing the literature in a structured manner. We first introduce and motivate data augmentation for NLP, and then discuss major methodologically representative approaches. Next, we highlight techniques that are used for popular NLP applications and tasks. We conclude by outlining current challenges and directions for future research. Overall, our paper aims to clarify the landscape of existing literature in data augmentation for NLP and motivate additional work in this area. We also present a GitHub repository with a paper list that will be continuously updated at https://github.com/styfeng/DataAug4NLP.

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mentioning

confidence: 99%

A Survey of Data Augmentation Approaches for NLP

Feng

Gangal

Wei

et al. 2021

Findings of the Association for Computational Linguistics: ACL-IJCNLP 2021

296

View full text Add to dashboard Cite

show abstract

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Data Augmentation Techniques for the Video Question Answering Task

Cited by 1 publication

References 23 publications

A Survey of Data Augmentation Approaches for NLP

A Survey of Data Augmentation Approaches for NLP

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