Human Focused Video Description

By Muhammad Usman Ghani Khan, Lei Zhang, Yoshihiko Gotoh. 2011

38 citations recorded by the source corpus.

Subfields: Computer Vision and Pattern Recognition, Natural Language Generation

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Citations in the corpus

Long-term recurrent convolutional networks for visual recognition and description (2014, methodology): “[11, 30, 17, 3, 6, 17, 41, 42] propose methods for generating sentence descriptions for video, but to our knowledge we present the first application of deep models to the video description task.”
A dataset for Movie Description (2015, background): “In recent years there has been an increased interest in automatically describing images [23, 39, 40, 50, 45, 40, 41, 34, 61, 22] and videos [37, 27, 8, 28, 32, 62, 16, 26, 64, 55] with natural language.”
Video Paragraph Captioning Using Hierarchical Recurrent Neural Networks (2015, methodology): “Following their work, several succeeding approaches [26, 20, 21, 15, 3] applied similar rule-based systems to datasets with larger numbers of objects and events, in different tasks and scenarios.”
Coherent Multi-sentence Video Description with Variable Level of Detail (2014, background): “Multi-sentence description, our first task, has been explored for videos [1, 6, 19], but open challenges remain, e.”
Translating Video Content to Natural Language Descriptions (2013, methodology): “Similarly, [11] uses templates to describe videos on the TREC Video summarization task.”
Spatio-Temporal Dynamics and Semantic Attribute Enriched Visual Encoding for Video Captioning (2019, result): “Whilst most of the prior work was restricted to constrained domains [25, 9], Krishnamoorthy et al.”
Learning to Describe Video with Weak Supervision by Exploiting Negative Sentential Information (2015, methodology): “First, some methods craft rule-based systems in which language generation is treated as an engineering task (Kojima, Tamura, and Fukunaga 2002; Lee et al. 2008; Khan, Zhang, and Gotoh 2011a; 2011b; Hanckmann, Schutte, and Burghouts 2012; Siddharth, Barbu, and Siskind 2014).”
Long-Term Recurrent Convolutional Networks for Visual Recognition and Description (2017, methodology): “Recent approaches to describing video with natural language have made use of templates, retrieval, or language models [11], [59], [60], [60], [61], [62], [63], [64].”
Visual to Text: Survey of Image and Video Captioning (2019, methodology): “recounted video events on the TREC Video summarization competition by designing a language template [39].”