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 51–100 of 280 papers

TitleStatusHype
Weakly-supervised Video Summarization using Variational Encoder-Decoder and Web PriorCode0
APES: Audiovisual Person Search in Untrimmed VideoCode0
What Is That Talk About? A Video-to-Text Summarization Dataset for Scientific PresentationsCode0
Your Interest, Your Summaries: Query-Focused Long Video SummarizationCode0
GPT2MVS: Generative Pre-trained Transformer-2 for Multi-modal Video SummarizationCode0
Vis-DSS: An Open-Source toolkit for Visual Data Selection and SummarizationCode0
Video Summarization using Deep Semantic FeaturesCode0
Adaptive frame selection in two dimensional convolutional neural network action recognitionCode0
Video Summarization with Long Short-term MemoryCode0
A Human-Annotated Video Dataset for Training and Evaluation of 360-Degree Video Summarization MethodsCode0
Video Summarization: Towards Entity-Aware CaptionsCode0
Visual Question Answering: which investigated applications?Code0
DeVAn: Dense Video Annotation for Video-Language ModelsCode0
FFNet: Video Fast-Forwarding via Reinforcement LearningCode0
Unsupervised Video Summarization via Iterative Training and Simplified GANCode0
Cluster-based Video Summarization with Temporal Context AwarenessCode0
Unsupervised Video Summarization via Attention-Driven Adversarial LearningCode0
Towards Practical and Efficient Long Video SummaryCode0
ERA: Entity Relationship Aware Video Summarization with Wasserstein GANCode0
An Integrated Framework for Multi-Granular Explanation of Video SummarizationCode0
Siamese Tracking with Lingual Object ConstraintsCode0
Spatio-Temporal Stability Analysis in Satellite Image Times SeriesCode0
Summarizing Videos with AttentionCode0
UBiSS: A Unified Framework for Bimodal Semantic Summarization of VideosCode0
Rethinking the Evaluation of Video SummariesCode0
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