List of participants of MSU SBD

MSU SBD Benchmark 2020

Click on the labels to sort the table.

Name Detects gradual transitions Free Open source Uses machine learning
Saeid Dadkhan No Yes Yes No
MaxReimann No Yes Yes Yes
aysebil No Yes Yes Yes
PyScene Yes Yes Yes No
VQMT Yes No No No
FFmpeg Yes Yes Yes No
johmathe No Yes Yes No
NITS-CV-Lab-v1.0 No Yes Yes No
GStreamer 1.16.2 No Yes Yes No

aysebil

Version: -

Added to the benchmark by: MSU

Parameters:

Links: GitHub

FFmpeg v4.2

Version: v4.2

Added to the benchmark by: MSU

Parameters:

Links: Documentation

johmathe

Version: -

Added to the benchmark by: MSU

Parameters:

Links: GitHub

Max Remain

Version: -

Added to the benchmark by: MSU

Parameters:

Links: GitHub

PyScene v0.5.4

Version: v0.5.4

Added to the benchmark by: MSU

Command: scenedetect -i {input} -o {output} detect-content list-scenes

Links: Documentation

PyScene v0.5.4 (thr = 27)

Version: v0.5.4

Added to the benchmark by: submitted by authors

Command: scenedetect -i {input} -o {output} detect-content -t 27 list-scenes

Links: Documentation

Saeid Dadkhan

Version: -

Added to the benchmark by: MSU

Parameters:

Links: GitHub

VQMT

Version: v1.2

Added to the benchmark by: MSU

Parameters:

Links: Information

NITS-CV-Lab-v1.0

Version: v1.0

Added to the benchmark by: submitted by authors

Parameters:

Links: GitHub

Paper: Singh, Alok, Dalton Meitei Thounaojam, and Saptarshi Chakraborty. "A novel automatic shot boundary detection algorithm: robust to illumination and motion effect." Signal, Image and Video Processing (2019): 1-9. https://doi.org/10.1007/s11760-019-01593-3

GStreamer 1.16.2

Version: v1.16.2

Added to the benchmark by: submitted by authors

Command: gst-launch-1.0 -v filesrc location={input} ! decodebin ! scenechange ! theoraenc ! fakesink

Links: Documentation

28 Dec 2020
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