It’s Just Another Day: Unique Video Captioning by Discriminitive Prompting

Abstract Long videos contain many repeating actions, events and shots. These repetitions are frequently given identical captions, which makes it difficult to retrieve the exact desired clip using a text search. In this paper, we formulate the problem of unique captioning: Given multiple clips with the same caption, we generate a new caption for each clip that uniquely identifies it. We propose Captioning by Discriminative Prompting (CDP), which predicts a property that can separate identically captioned clips, and use it to generate unique captions. We introduce two benchmarks for unique captioning, based on egocentric footage and timeloop movies – where repeating actions are common. We demonstrate that captions generated by CDP improve text-to-video R@1 by 15% for egocentric videos and 10% in timeloop movies. https://tobyperrett.github.io/its-just-another-day

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Publication Details

Journal
International Journal of Computer Vision
Published
2026-01-13
DOI
https://doi.org/10.1007/s11263-025-02664-4
Primary Topic
Multimodal Machine Learning Applications
Type
article
Field-Weighted Citation Impact
0.00

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article

It’s Just Another Day: Unique Video Captioning by Discriminitive Prompting

Dima Damen, Toby Perrett, Tengda Han, Andrew Zisserman
International Journal of Computer Vision
Multimodal Machine Learning Applications
article

It’s Just Another Day: Unique Video Captioning by Discriminitive Prompting

Dima Damen, Toby Perrett, Tengda Han, Andrew Zisserman
article en

Abstract

Abstract Long videos contain many repeating actions, events and shots. These repetitions are frequently given identical captions, which makes it difficult to retrieve the exact desired clip using a text search. In this paper, we formulate the problem of unique captioning: Given multiple clips with the same caption, we generate a new caption for each clip that uniquely identifies it. We propose Captioning by Discriminative Prompting (CDP), which predicts a property that can separate identically captioned clips, and use it to generate unique captions. We introduce two benchmarks for unique captioning, based on egocentric footage and timeloop movies – where repeating actions are common. We demonstrate that captions generated by CDP improve text-to-video R@1 by 15% for egocentric videos and 10% in timeloop movies. https://tobyperrett.github.io/its-just-another-day

International Journal of Computer VisionVol. 134(2)
University of Bristol (GB), University of Oxford (GB)
Engineering and Physical Sciences Research Council
Reduced inequalities
Openalex Percentile: Top 92%
Multimodal Machine Learning Applications
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