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| Auteurs principaux: | , , , , |
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| Format: | Preprint |
| Publié: |
2024
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| Sujets: | |
| Accès en ligne: | https://arxiv.org/abs/2401.16076 |
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| _version_ | 1866913214819729408 |
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| author | Bretti, Carlo Mettes, Pascal Koops, Hendrik Vincent Odijk, Daan van Noord, Nanne |
| author_facet | Bretti, Carlo Mettes, Pascal Koops, Hendrik Vincent Odijk, Daan van Noord, Nanne |
| contents | Creating a trailer requires carefully picking out and piecing together brief enticing moments out of a longer video, making it a challenging and time-consuming task. This requires selecting moments based on both visual and dialogue information. We introduce a multi-modal method for predicting the trailerness to assist editors in selecting trailer-worthy moments from long-form videos. We present results on a newly introduced soap opera dataset, demonstrating that predicting trailerness is a challenging task that benefits from multi-modal information. Code is available at https://github.com/carlobretti/cliffhanger |
| format | Preprint |
| id |
arxiv_https___arxiv_org_abs_2401_16076 |
| institution | arXiv |
| publishDate | 2024 |
| record_format | arxiv |
| spellingShingle | Find the Cliffhanger: Multi-Modal Trailerness in Soap Operas Bretti, Carlo Mettes, Pascal Koops, Hendrik Vincent Odijk, Daan van Noord, Nanne Computer Vision and Pattern Recognition Multimedia Creating a trailer requires carefully picking out and piecing together brief enticing moments out of a longer video, making it a challenging and time-consuming task. This requires selecting moments based on both visual and dialogue information. We introduce a multi-modal method for predicting the trailerness to assist editors in selecting trailer-worthy moments from long-form videos. We present results on a newly introduced soap opera dataset, demonstrating that predicting trailerness is a challenging task that benefits from multi-modal information. Code is available at https://github.com/carlobretti/cliffhanger |
| title | Find the Cliffhanger: Multi-Modal Trailerness in Soap Operas |
| topic | Computer Vision and Pattern Recognition Multimedia |
| url | https://arxiv.org/abs/2401.16076 |