Papers › Spatio-Temporal CNN baseline method for the Sports Video Task of MediaEval 2021 benchmark
Spatio-Temporal CNN baseline method for the Sports Video Task of MediaEval 2021 benchmark
Pierre-Etienne Martin
This paper presents the baseline method proposed for the Sports Video task part of the MediaEval 2021 benchmark. This task proposes a stroke detection and a stroke classification subtasks. This baseline addresses both subtasks. The spatio-temporal CNN architecture and the training process of the model are tailored according to the addressed subtask. The method has the purpose of helping the participants to solve the task and is not meant to reach stateof-the-art performance. Still, for the detection task, the baseline is performing better than the other participants, which stresses the difficulty of such a task.
Code
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Tasks
Results from the paper archive 2025-07-28
| Task | Dataset | Model | Metric | Value | Rank at snapshot | Leaderboard | Report |
|---|---|---|---|---|---|---|---|
| Action Classification | TTStroke-21 ME21 | STCNN | Acc | 20.4 | #1 of 1 | Archive leaderboard | report |
| Action Detection | TTStroke-21 ME21 | STCNN | IoU | 0.144 | #1 of 2 | Archive leaderboard | report |
| Action Detection | TTStroke-21 ME21 | STCNN | mAP | 0.0173 | #1 of 2 | Archive leaderboard | report |
Ranks are positions in the archive's leaderboards as they stood at the 2025-07-28 snapshot. Results published since then are not among these rows, so a rank here is not a current standing.
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