mlsanityData to 14 Oct 2026

Spatio-Temporal CNN baseline method for the Sports Video Task of MediaEval 2021 benchmark

arXiv 2112.12074 ↗First posted 16 Dec 2021cs.CV cs.AI cs.LGcited by 3

Not on the map. Why?

Abstract (arXiv)

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.

Key facts. Cited by 3 papers in the map (data through 14 Oct 2026). Builds on 6 of its 21 references that are in the map. First posted on arXiv 16 Dec 2021.

Builds on

6 of 21 references.

References · 6

  1. 2017Quo Vadis, Action Recognition? A New Model and the Kinetics Datasetcited by 3,270
  2. 2014Two-Stream Convolutional Networks for Action Recognition in Videoscited by 1,068
  3. 2016Convolutional Two-Stream Network Fusion for Video Action Recognitioncited by 384
  4. 20182D/3D Pose Estimation and Action Recognition using Multitask Deep Learningcited by 103
  5. 2018LCR-Net++: Multi-person 2D and 3D Pose Detection in Natural Imagescited by 88
  6. 2021Three-Stream 3D/1D CNN for Fine-Grained Action Classification and Segmentation in Table Tenniscited by 5

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Cited by year

Citing papers per year: 2023: 3.

3 papers.

  1. 2023Sport Task: Fine Grained Action Detection and Classification of Table Tennis Strokes from Videos for MediaEval 2022cited by 2
  2. 2023Baseline Method for the Sport Task of MediaEval 2022 with 3D CNNs using Attention Mechanismscited by 1
  3. 2023Fine-Grained Action Detection with RGB and Pose Information using Two Stream Convolutional Networkscited by 1