activity
20202023
most citedThree-Stream 3D/1D CNN for Fine-Grained Action Classification and Segmentation in Table Tennis

13 citations · 16 across the 4 of their papers we have counts for

collaborators

4 papers

cs.AI2023★ 1 cited

Sport Task: Fine Grained Action Detection and Classification of Table Tennis Strokes from Videos for MediaEval 2022

Pierre-Etienne Martin, Jordan Calandre, Boris Mansencal +4

Sports video analysis is a widespread research topic. Its applications are very diverse, like events detection during a match, video summary, or fine-grained movement analysis of a…

cs.CV2021★ 2 cited

Sports Video: Fine-Grained Action Detection and Classification of Table Tennis Strokes from Videos for MediaEval 2021

Pierre-Etienne Martin, Jordan Calandre, Boris Mansencal +4

Sports video analysis is a prevalent research topic due to the variety of application areas, ranging from multimedia intelligent devices with user-tailored digests up to analysis o…

cs.CV2021★ 13 cited

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

Pierre-Etienne Martin, Jenny Benois-Pineau, Renaud Péteri +1

This paper proposes a fusion method of modalities extracted from video through a three-stream network with spatio-temporal and temporal convolutions for fine-grained action classif…

cs.CV2020

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

Pierre-Etienne Martin, Jenny Benois-Pineau, Renaud Péteri +1

The paper addresses the problem of recognition of actions in video with low inter-class variability such as Table Tennis strokes. Two stream, "twin" convolutional neural networks a…