Pith. sign in

REVIEW

Find the Cliffhanger: Multi-Modal Trailerness in Soap Operas

Not yet reviewed by Pith; the record is open.

Re-run · record.json Download PDF Read on arXiv ↗

This paper has not been read by Pith yet. Machine review is queued; the pith claim, tier, and objections will appear here once it completes.

SPECIMEN: schema-true, not a live event

T0 review · schema-true

One-sentence machine reading of the paper's core claim.

pith:XXXXXXXX · record.json · timestamp

arxiv 2401.16076 v1 pith:MJ5C5I3Q submitted 2024-01-29 cs.CV cs.MM

Carlo Bretti , Pascal Mettes , Hendrik Vincent Koops , Daan Odijk , Nanne van Noord This is my paper · ORCID
classification cs.CVcs.MM
keywords momentsmulti-modaltrailernesschallengingcliffhangerinformationpredictingrequires
verification ladder T0 review T1 audit T2 compute T3 formal
0 comments
read the original abstract

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

Discussion (0). Continue with ORCID to comment.

Pith tools