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 201–225 of 280 papers

TitleStatusHype
A Novel Technique for Evidence based Conditional Inference in Deep Neural Networks via Latent Feature Perturbation—0
Discriminative Feature Learning for Unsupervised Video SummarizationCode0
A Framework towards Domain Specific Video Summarization—0
Vis-DSS: An Open-Source toolkit for Visual Data Selection and SummarizationCode0
A Dataset and Preliminary Results for Umpire Pose Detection Using SVM Classification of Deep Features—0
Pack and Detect: Fast Object Detection in Videos Using Region-of-Interest Packing—0
Diverse and Coherent Paragraph Generation from Images—0
Retrospective Encoders for Video Summarization—0
Weakly-supervised Video Summarization using Variational Encoder-Decoder and Web PriorCode0
Improving Sequential Determinantal Point Processes for Supervised Video Summarization—0
Query-Conditioned Three-Player Adversarial Network for Video Summarization—0
How Local is the Local Diversity? Reinforcing Sequential Determinantal Point Processes with Dynamic Ground Sets for Supervised Video Summarization—0
HSA-RNN: Hierarchical Structure-Adaptive RNN for Video Summarization—0
A Memory Network Approach for Story-Based Temporal Summarization of 360° Videos—0
Video Summarization by Learning from Unpaired Data—0
Video Summarization Using Fully Convolutional Sequence Networks—0
FFNet: Video Fast-Forwarding via Reinforcement LearningCode0
A Memory Network Approach for Story-based Temporal Summarization of 360° Videos—0
Dilated Temporal Relational Adversarial Network for Generic Video Summarization—0
Viewpoint-aware Video Summarization—0
Segmentation of Bleeding Regions in Wireless Capsule Endoscopy Images an Approach for inside Capsule Video Summarization—0
Do Less, Get More: Streaming Submodular Maximization with Subsampling—0
Unsupervised Object-Level Video Summarization with Online Motion Auto-Encoder—0
Deep Reinforcement Learning for Unsupervised Video Summarization with Diversity-Representativeness RewardCode0
Subset Selection and Summarization in Sequential Data—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
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