# Query-Focused Extractive Video Summarization

arXiv: https://arxiv.org/abs/1607.05177 · HTML: https://mlsanity.com/paper/1607.05177/

## Key facts

- Cited by 26 papers in the map (data through 14 Oct 2026).
- First posted on arXiv 18 Jul 2016.

## Built on by (most cited first, 26 of 26)

- [EgoVLPv2: Egocentric Video-Language Pre-training with Fusion in the Backbone](https://mlsanity.com/paper/2307.05463/) (2023)
- [CLIP-It! Language-Guided Video Summarization](https://mlsanity.com/paper/2107.00650/) (2021)
- [Video Summarization Using Deep Neural Networks: A Survey](https://mlsanity.com/paper/2101.06072/) (2021)
- [An Outlook into the Future of Egocentric Vision](https://mlsanity.com/paper/2308.07123/) (2023)
- [PRISM: A Rich Class of Parameterized Submodular Information Measures for Guided Subset Selection](https://mlsanity.com/paper/2103.00128/) (2021)
- [Submodularity In Machine Learning and Artificial Intelligence](https://mlsanity.com/paper/2202.00132/) (2022)
- [TL;DW? Summarizing Instructional Videos with Task Relevance & Cross-Modal Saliency](https://mlsanity.com/paper/2208.06773/) (2022)
- [Scaling Up Video Summarization Pretraining with Large Language Models](https://mlsanity.com/paper/2404.03398/) (2024)
- [DeepQAMVS: Query-Aware Hierarchical Pointer Networks for Multi-Video Summarization](https://mlsanity.com/paper/2105.06441/) (2021)
- [DNS: Determinantal Point Process Based Neural Network Sampler for Ensemble Reinforcement Learning](https://mlsanity.com/paper/2201.13357/) (2022)
- [Unsupervised Modality-Transferable Video Highlight Detection with Representation Activation Sequence Learning](https://mlsanity.com/paper/2403.09401/) (2024)
- [How Good is a Video Summary? A New Benchmarking Dataset and Evaluation Framework Towards Realistic Video Summarization](https://mlsanity.com/paper/2101.10514/) (2021)
- [PR-Net: Preference Reasoning for Personalized Video Highlight Detection](https://mlsanity.com/paper/2109.01799/) (2021)
- [Video Summarization Overview](https://mlsanity.com/paper/2210.11707/) (2022)
- [Spiking Variational Graph Representation Inference for Video Summarization](https://mlsanity.com/paper/2508.15389/) (2025)
- [Multimodal Frame-Scoring Transformer for Video Summarization](https://mlsanity.com/paper/2207.01814/) (2022)
- [SD-VSum: A Method and Dataset for Script-Driven Video Summarization](https://mlsanity.com/paper/2505.03319/) (2025)
- [Prompts to Summaries: Zero-Shot Language-Guided Video Summarization with Large Language and Video Models](https://mlsanity.com/paper/2506.10807/) (2025)
- [Language-Guided Graph Representation Learning for Video Summarization](https://mlsanity.com/paper/2511.10953/) (2025)
- [Show Me What I Like: Detecting User-Specific Video Highlights Using Content-Based Multi-Head Attention](https://mlsanity.com/paper/2207.08352/) (2022)
- [Your Interest, Your Summaries: Query-Focused Long Video Summarization](https://mlsanity.com/paper/2410.14087/) (2024)
- [Augmenting Moment Retrieval: Zero-Dependency Two-Stage Learning](https://mlsanity.com/paper/2510.19622/) (2025)
- [Query-centric Audio-Visual Cognition Network for Moment Retrieval, Segmentation and Step-Captioning](https://mlsanity.com/paper/2412.13543/) (2024)
- [Language-guided Recursive Spatiotemporal Graph Modeling for Video Summarization](https://mlsanity.com/paper/2509.05604/) (2025)
- [SD-MVSum: Script-Driven Multimodal Video Summarization Method and Datasets](https://mlsanity.com/paper/2510.05652/) (2025)
- [LVSum: A Benchmark for Timestamp-Aware Long Video Summarization](https://mlsanity.com/paper/2604.10024/) (2026)

## Abstract (arXiv)

Video data is explosively growing. As a result of the "big video data", intelligent algorithms for automatic video summarization have re-emerged as a pressing need. We develop a probabilistic model, Sequential and Hierarchical Determinantal Point Process (SH-DPP), for query-focused extractive video summarization. Given a user query and a long video sequence, our algorithm returns a summary by selecting key shots from the video. The decision to include a shot in the summary depends on the shot's relevance to the user query and importance in the context of the video, jointly. We verify our approach on two densely annotated video datasets. The query-focused video summarization is particularly useful for search engines, e.g., to display snippets of videos.