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Video Summarization

Video Summarization aims to generate a short synopsis that summarizes the video content by selecting its most informative and important parts. The produced summary is usually composed of a set of representative video frames (a.k.a. video key-frames), or video fragments (a.k.a. video key-fragments) that have been stitched in chronological order to form a shorter video. The former type of a video summary is known as video storyboard, and the latter type is known as video skim.

Source: Video Summarization Using Deep Neural Networks: A Survey Image credit: iJRASET

Papers

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Showing 201–225 of 280 papers

TitleStatusHype
"Previously on ..." From Recaps to Story Summarization—0
Previously on ... From Recaps to Story Summarization—0
Prompts to Summaries: Zero-Shot Language-Guided Video Summarization—0
Query-Aware Sparse Coding for Multi-Video Summarization—0
Query-based Video Summarization with Pseudo Label Supervision—0
Query-centric Audio-Visual Cognition Network for Moment Retrieval, Segmentation and Step-Captioning—0
Query-Conditioned Three-Player Adversarial Network for Video Summarization—0
Query-Focused Extractive Video Summarization—0
Query-Focused Video Summarization: Dataset, Evaluation, and A Memory Network Based Approach—0
Query Twice: Dual Mixture Attention Meta Learning for Video Summarization—0
R^2-Tuning: Efficient Image-to-Video Transfer Learning for Video Temporal Grounding—0
R^2-Tuning: Efficient Image-to-Video Transfer Learning for Video Temporal Grounding—0
Realistic Video Summarization through VISIOCITY: A New Benchmark and Evaluation Framework—0
Realizing Video Summarization from the Path of Language-based Semantic Understanding—0
Real-time Video Summarization on Commodity Hardware—0
Recognizing Micro-Actions and Reactions From Paired Egocentric Videos—0
Reconstructive Sequence-Graph Network for Video Summarization—0
REGen: Multimodal Retrieval-Embedded Generation for Long-to-Short Video Editing—0
Reinforcement Learning for Ultrasound Image Analysis A Comprehensive Review of Advances and Applications—0
Relational Reasoning Over Spatial-Temporal Graphs for Video Summarization—0
Representative Selection for Big Data via Sparse Graph and Geodesic Grassmann Manifold Distance—0
Retrospective Encoders for Video Summarization—0
Role of Audio in Audio-Visual Video Summarization—0
Saliency-based Video Summarization for Face Anti-spoofing—0
SalSum: Saliency-based Video Summarization using Generative Adversarial Networks—0
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All datasetsSumMeTvSumShot2Story20KQuery-Focused Video Summarization DatasetMr. HiSumVideoXum

Benchmark Results

#ModelMetricClaimedVerifiedStatus
1PGL-SUMF1-score (Canonical)55.6—Unverified
2RR-STGF1-score (Canonical)54.5—Unverified
3DSNetF1-score (Canonical)53—Unverified
4VASNetF1-score (Canonical)49.71—Unverified
5M-AVSF1-score (Canonical)44.4—Unverified
6CSTAKendall's Tau0.25—Unverified
#ModelMetricClaimedVerifiedStatus
1RR-STGF1-score (Canonical)63—Unverified
2DSNetF1-score (Canonical)62.1—Unverified
3VASNetF1-score (Canonical)61.42—Unverified
4PGL-SUMF1-score (Canonical)61—Unverified
5M-AVSF1-score (Canonical)61—Unverified
6CSTAKendall's Tau0.19—Unverified
#ModelMetricClaimedVerifiedStatus
1Shotluck-Holmes (3.1B)CIDEr152.3—Unverified
2Shotluck-Holmes (3.1B)CIDEr63.2—Unverified
3SUM-shotCIDEr8.6—Unverified
#ModelMetricClaimedVerifiedStatus
1EgoVLPv2F1 (avg)52.08—Unverified
2EgoVLPF1 (avg)49.72—Unverified
#ModelMetricClaimedVerifiedStatus
1PGL-SUMMAP (50%)61.6—Unverified
#ModelMetricClaimedVerifiedStatus
1VTSUM-BLIP1 shot Micro-F123.5—Unverified