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Models/MMV

MMV

Reported on 8 benchmarks across 4 tasks · 1 paper · 4 SOTA

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

Robots3 results

Activity RecognitiononKinetics-600
Top-1 Accuracy· 2020-06-29
55.5
best: 87.8 (Florence)
SOTA
Self-Supervised MultiModal Versatile Networks arXiv:2006.16228
Activity RecognitiononHMDB51 (finetuned)
Top-1 Accuracy· 2020-06-29
70.1
best: 77.8 (BraVe:V-FA (TSM-50x2))
SOTA
Self-Supervised MultiModal Versatile Networks arXiv:2006.16228
Activity RecognitiononUCF101 (finetuned)
3-fold Accuracy· 2020-06-29
91.5
best: 95.7 (BraVe:V-FA (TSM-50x2))
Self-Supervised MultiModal Versatile Networks arXiv:2006.16228

Time Series3 results

Action RecognitiononKinetics-600
Top-1 Accuracy· 2020-06-29
55.5
best: 87.8 (Florence)
SOTA
Self-Supervised MultiModal Versatile Networks arXiv:2006.16228
Action RecognitiononHMDB51 (finetuned)
Top-1 Accuracy· 2020-06-29
70.1
best: 77.8 (BraVe:V-FA (TSM-50x2))
SOTA
Self-Supervised MultiModal Versatile Networks arXiv:2006.16228
Action RecognitiononUCF101 (finetuned)
3-fold Accuracy· 2020-06-29
91.5
best: 95.7 (BraVe:V-FA (TSM-50x2))
Self-Supervised MultiModal Versatile Networks arXiv:2006.16228

Audio1 result

Audio ClassificationonAudioSet
Test mAP· 2020-06-29
0.309
best: 0.558 (OmniVec2)
Self-Supervised MultiModal Versatile Networks arXiv:2006.16228

Methodology1 result

ClassificationonAudioSet
Test mAP· 2020-06-29
0.309
best: 0.558 (OmniVec2)
Self-Supervised MultiModal Versatile Networks arXiv:2006.16228