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Two Stream Network for Stroke Detection in Table Tennis

12/16/2021

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by Anam Zahra, et al.

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This paper presents a table tennis stroke detection method from videos. The method relies on a two-stream Convolutional Neural Network processing in parallel the RGB Stream and its computed optical flow. The method has been developed as part of the MediaEval 2021 benchmark for the Sport task. Our contribution did not outperform the provided baseline on the test set but has performed the best among the other participants with regard to the mAP metric.

Anam Zahra
1 publication
Pierre-Etienne Martin
9 publications

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∙ 02/06/2023

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Dance with Flow: Two-in-One Stream Action Detection

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∙ 11/20/2020

3D attention mechanism for fine-grained classification of table tennis strokes using a Twin Spatio-Temporal Convolutional Neural Networks

The paper addresses the problem of recognition of actions in video with ...

0 Pierre-Etienne Martin, et al. ∙

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∙ 02/06/2023

Baseline Method for the Sport Task of MediaEval 2022 with 3D CNNs using Attention Mechanisms

This paper presents the baseline method proposed for the Sports Video ta...

0 Pierre-Etienne Martin, et al. ∙

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∙ 09/29/2021

Three-Stream 3D/1D CNN for Fine-Grained Action Classification and Segmentation in Table Tennis

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11 Pierre-Etienne Martin, et al. ∙

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∙ 11/07/2020

A Multi-stream Convolutional Neural Network for Micro-expression Recognition Using Optical Flow and EVM

Micro-expression (ME) recognition plays a crucial role in a wide range o...

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∙ 03/29/2018

Two-Stream Neural Networks for Tampered Face Detection

We propose a two-stream network for face tampering detection. We train G...

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