PyScene-v2

Reported on 2 benchmarks across 1 task · 1 paper · 2 SOTA

Note: results are matched by exact model name. Different papers may use the same name for different model variants.

Computer Vision2 results

Video SegmentationonMSU Shot Boundary Detection Benchmark
F score· 2017-05-09
0.7534
best: 0.847 (NITS-CV-Lab-v1.0)
SOTA
Large-scale, Fast and Accurate Shot Boundary Detection through Spatio-temporal Convolutional Neural Networks arXiv:1705.03281
Video SegmentationonMSU Shot Boundary Detection Benchmark
FPS· 2017-05-09
86
best: 163 (GStreamer)
SOTA
Large-scale, Fast and Accurate Shot Boundary Detection through Spatio-temporal Convolutional Neural Networks arXiv:1705.03281