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Models/BallSeg

BallSeg

Reported on 15 benchmarks across 1 task · 1 paper · 9 SOTA

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

Computer Vision15 results

Object TrackingonTennis
Accuracy (%)· 2020-07-23
57.5
best: 91.8 (WASB (Step=1))
SOTA
Real-time CNN-based Segmentation Architecture for Ball Detection in a Single View Setup arXiv:2007.11876
Object TrackingonTennis
Average Precision (%)· 2020-07-23
56.8
best: 94.2 (WASB (Step=1))
SOTA
Real-time CNN-based Segmentation Architecture for Ball Detection in a Single View Setup arXiv:2007.11876
Object TrackingonTennis
F1 (%)· 2020-07-23
71.7
best: 95.6 (WASB (Step=1))
SOTA
Real-time CNN-based Segmentation Architecture for Ball Detection in a Single View Setup arXiv:2007.11876
Object TrackingonBadminton
Accuracy (%)· 2020-07-23
72.2
best: 89 (WASB (Step=1))
SOTA
Real-time CNN-based Segmentation Architecture for Ball Detection in a Single View Setup arXiv:2007.11876
Object TrackingonBadminton
Average Precision (%)· 2020-07-23
68.4
best: 91.6 (WASB (Step=1))
SOTA
Real-time CNN-based Segmentation Architecture for Ball Detection in a Single View Setup arXiv:2007.11876
Object TrackingonBadminton
F1 (%)· 2020-07-23
79.9
best: 93.1 (WASB (Step=1))
SOTA
Real-time CNN-based Segmentation Architecture for Ball Detection in a Single View Setup arXiv:2007.11876
Object TrackingonBasketball
Accuracy (%)· 2020-07-23
20.5
best: 73.4 (WASB (Step=1))
SOTA
Real-time CNN-based Segmentation Architecture for Ball Detection in a Single View Setup arXiv:2007.11876
Object TrackingonBasketball
Average Precision (%)· 2020-07-23
5.3
best: 77.1 (WASB (Step=1))
SOTA
Real-time CNN-based Segmentation Architecture for Ball Detection in a Single View Setup arXiv:2007.11876
Object TrackingonBasketball
F1 (%)· 2020-07-23
16.8
best: 82.6 (WASB (Step=1))
SOTA
Real-time CNN-based Segmentation Architecture for Ball Detection in a Single View Setup arXiv:2007.11876
Object TrackingonSoccer
Accuracy (% )· 2020-07-23
92.6
best: 97.9 (WASB (Step=3))
Real-time CNN-based Segmentation Architecture for Ball Detection in a Single View Setup arXiv:2007.11876
Object TrackingonSoccer
Average Precision (%)· 2020-07-23
20
best: 86.2 (WASB (Step=1))
Real-time CNN-based Segmentation Architecture for Ball Detection in a Single View Setup arXiv:2007.11876
Object TrackingonSoccer
F1 (%)· 2020-07-23
36.1
best: 88.3 (WASB (Step=3))
Real-time CNN-based Segmentation Architecture for Ball Detection in a Single View Setup arXiv:2007.11876
Object TrackingonVolleyball
Accuracy (%)· 2020-07-23
17.5
best: 80 (WASB (Step=1))
Real-time CNN-based Segmentation Architecture for Ball Detection in a Single View Setup arXiv:2007.11876
Object TrackingonVolleyball
Average Precision (%)· 2020-07-23
8.5
best: 83.2 (WASB (Step=1))
Real-time CNN-based Segmentation Architecture for Ball Detection in a Single View Setup arXiv:2007.11876
Object TrackingonVolleyball
F1 (%)· 2020-07-23
19.5
best: 88 (WASB (Step=1))
Real-time CNN-based Segmentation Architecture for Ball Detection in a Single View Setup arXiv:2007.11876