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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Benchmark Results

#ModelMetricClaimedVerifiedStatus
1PGL-SUMF1-score (Canonical)55.6Unverified
2RR-STGF1-score (Canonical)54.5Unverified
3DSNetF1-score (Canonical)53Unverified
4VASNetF1-score (Canonical)49.71Unverified
5M-AVSF1-score (Canonical)44.4Unverified
6CSTAKendall's Tau0.25Unverified
#ModelMetricClaimedVerifiedStatus
1RR-STGF1-score (Canonical)63Unverified
2DSNetF1-score (Canonical)62.1Unverified
3VASNetF1-score (Canonical)61.42Unverified
4M-AVSF1-score (Canonical)61Unverified
5PGL-SUMF1-score (Canonical)61Unverified
6CSTAKendall's Tau0.19Unverified
#ModelMetricClaimedVerifiedStatus
1Shotluck-Holmes (3.1B)CIDEr152.3Unverified
2Shotluck-Holmes (3.1B)CIDEr63.2Unverified
3SUM-shotCIDEr8.6Unverified
#ModelMetricClaimedVerifiedStatus
1EgoVLPv2F1 (avg)52.08Unverified
2EgoVLPF1 (avg)49.72Unverified
#ModelMetricClaimedVerifiedStatus
1PGL-SUMMAP (50%)61.6Unverified
#ModelMetricClaimedVerifiedStatus
1VTSUM-BLIP1 shot Micro-F123.5Unverified