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 76–100 of 280 papers

TitleStatusHype
SD-VSum: A Method and Dataset for Script-Driven Video SummarizationCode0
SELF-VS: Self-supervised Encoding Learning For Video SummarizationCode0
Multi-Stream Dynamic Video SummarizationCode0
Query-adaptive Video Summarization via Quality-aware Relevance EstimationCode0
A Challenging Multimodal Video Summary: Simultaneously Extracting and Generating Keyframe-Caption Pairs from VideoCode0
Does SpatioTemporal information benefit Two video summarization benchmarks?Code0
Enhancing Video Summarization with Context AwarenessCode0
Integrate the temporal scheme for unsupervised video summarization via attention mechanismCode0
Iterative Projection and Matching: Finding Structure-preserving Representatives and Its Application to Computer VisionCode0
CLIP-It! Language-Guided Video SummarizationCode0
Temporal Tessellation: A Unified Approach for Video AnalysisCode0
ILS-SUMM: Iterated Local Search for Unsupervised Video SummarizationCode0
Attention is all you need for Videos: Self-attention based Video Summarization using Universal Transformers—0
Discovery of Shared Semantic Spaces for Multi-Scene Video Query and Summarization—0
Detecting Engagement in Egocentric Video—0
A Survey on Recent Advances of Computer Vision Algorithms for Egocentric Video—0
A Multi-stage deep architecture for summary generation of soccer videos—0
Demystifying Multi-Faceted Video Summarization: Tradeoff Between Diversity,Representation, Coverage and Importance—0
DeepQAMVS: Query-Aware Hierarchical Pointer Networks for Multi-Video Summarization—0
Cycle-SUM: Cycle-consistent Adversarial LSTM Networks for Unsupervised Video Summarization—0
A Survey on Patch-based Synthesis: GPU Implementation and Optimization—0
A Memory Network Approach for Story-Based Temporal Summarization of 360° Videos—0
CSTA: CNN-based Spatiotemporal Attention for Video Summarization—0
Creating Summaries from User Videos—0
Co-Regularized Deep Representations for Video Summarization—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