SOTAVerified

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 176–200 of 280 papers

TitleStatusHype
Video Summarization in a Multi-View Camera Network—0
Video Summarization Overview—0
Video Summarization: Study of various techniques—0
Video Summarization Techniques: A Comprehensive Review—0
A Mobile Robot Generating Video Summaries of Seniors' Indoor Activities—0
Video Summarization through Reinforcement Learning with a 3D Spatio-Temporal U-Net—0
Video Summarization Using Deep Neural Networks: A Survey—0
Video Summarization using Denoising Diffusion Probabilistic Model—0
Video Summarization Using Fully Convolutional Sequence Networks—0
Video Summarization via Actionness Ranking—0
Video Summarization with Attention-Based Encoder-Decoder Networks—0
Video Summarization with Large Language Models—0
Video-Teller: Enhancing Cross-Modal Generation with Fusion and Decoupling—0
Viewpoint-aware Video Summarization—0
Visual Recognition by Counting Instances: A Multi-Instance Cardinality Potential Kernel—0
Visual Summarization of Scholarly Videos using Word Embeddings and Keyphrase Extraction—0
VSCAN: An Enhanced Video Summarization using Density-based Spatial Clustering—0
Weakly Supervised Video Summarization by Hierarchical Reinforcement Learning—0
Recognizing Micro-Actions and Reactions From Paired Egocentric Videos—0
A Dataset and Preliminary Results for Umpire Pose Detection Using SVM Classification of Deep Features—0
A Framework towards Domain Specific Video Summarization—0
A General Framework for Edited Video and Raw Video Summarization—0
Agent-based Video Trimming—0
A Graph-based Ranking Approach to Extract Key-frames for Static Video Summarization—0
A Memory Network Approach for Story-based Temporal Summarization of 360° Videos—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