arXiv:2112.12074
공식 코드 · Papers with Code
Spatio-Temporal CNN baseline method for the Sports Video Task of MediaEval 2021 benchmark
원문 초록
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.
함께 살펴볼 논문
공통 태그를 근거로 연결했습니다. 실제 인용 관계나 논문의 우수성을 뜻하지 않습니다.
Progression-Guided Temporal Action Detection in Videos
ADM-Loc: Actionness Distribution Modeling for Point-supervised Temporal Action Localization
SkeleTR: Towrads Skeleton-based Action Recognition in the Wild
From Play to Replay: Composed Video Retrieval for Temporally Fine-Grained Videos
Spatio-Temporal Joint Density Driven Learning for Skeleton-Based Action Recognition
Multi-Stage Speaker Diarization for Noisy Classrooms
토론
이 논문과 연결된 포럼 글이 아직 없습니다.