Research map / Video / Video segmentation and tracking
Predicting Soccer Highlights from Spatio-Temporal Match Event Streams
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Measured effects reported in the paper
| What was changed | Where | Measured | Effect |
|---|---|---|---|
| add indirect (attempt-based) probability estimation (ablation) | POGBA vs SpatTempDir · Soccer highlight prediction (25 matches, leave-one-match-out) | F1: 0.50 -> 0.51 | Helped |
| add indirect probability estimation to spatial-only model (ablation) | SpatDir · Soccer highlight prediction (25 matches, leave-one-match-out) | F1: 0.36 -> 0.40 | Helped |
| add spatio-temporal data to direct model (ablation) | SpatDir · Soccer highlight prediction (25 matches, leave-one-match-out) | F1: 0.36 -> 0.50 | Helped |
| add spatio-temporal data to indirect model (ablation) | SpatIndir · Soccer highlight prediction (25 matches, leave-one-match-out) | F1: 0.40 -> 0.51 | Helped |
| add indirect estimation to spatial-only model (ablation) | SpatDir · Soccer highlight prediction (25 matches, leave-one-match-out) | precision: 0.34 -> 0.36 | Mixed |
| use DTW instead of Euclidean distance in nearest neighbors (ablation) | goal attempt predictor · Goal attempt prediction | AUROC: 0.6 -> 0.8 | Helped |
| swap probabilistic classifier for P(goal|attempt) (ablation) | POGBA · Goal probability estimation | AUROC: 0.73 to 0.79 | No clear effect |
Closest papers by meaning
- Towards Universal Soccer Video Understanding (CVPR 2025 · similarity 0.85)
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