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

Recently AddedMost HypedMost ActiveNeeds VerificationMost Verified

Showing 226–250 of 280 papers

TitleStatusHype
Scaling Submodular Maximization via Pruned Submodularity Graphs—0
Scaling Up Video Summarization Pretraining with Large Language Models—0
Scene Summarization: Clustering Scene Videos into Spatially Diverse Frames—0
Segmentation of Bleeding Regions in Wireless Capsule Endoscopy Images an Approach for inside Capsule Video Summarization—0
Self-Attention Based Generative Adversarial Networks For Unsupervised Video Summarization—0
Semantics for Large-Scale Multimedia: New Challenges for NLP—0
Semantic Video Trailers—0
Sequence-to-Segment Networks for Segment Detection—0
Show and Recall: Learning What Makes Videos Memorable—0
Distance Metric-Based Learning with Interpolated Latent Features for Location Classification in Endoscopy Image and Video—0
Story-Driven Summarization for Egocentric Video—0
Iterative Projection and Matching: Finding Structure-preserving Representatives and Its Application to Computer VisionCode0
Multi-Stream Dynamic Video SummarizationCode0
Does SpatioTemporal information benefit Two video summarization benchmarks?Code0
Your Interest, Your Summaries: Query-Focused Long Video SummarizationCode0
SD-VSum: A Method and Dataset for Script-Driven Video SummarizationCode0
Discriminative Feature Learning for Unsupervised Video SummarizationCode0
Unsupervised multi-latent space reinforcement learning framework for video summarization in ultrasound imagingCode0
ILS-SUMM: Iterated Local Search for Unsupervised Video SummarizationCode0
SELF-VS: Self-supervised Encoding Learning For Video SummarizationCode0
Weakly-supervised Video Summarization using Variational Encoder-Decoder and Web PriorCode0
Video Summarization with Long Short-term MemoryCode0
Unsupervised Video Summarization via Iterative Training and Simplified GANCode0
GPT2MVS: Generative Pre-trained Transformer-2 for Multi-modal Video SummarizationCode0
FFNet: Video Fast-Forwarding via Reinforcement LearningCode0
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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
4M-AVSF1-score (Canonical)61—Unverified
5PGL-SUMF1-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