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Found 4 papers, 1 papers with code
Ice hockey player identification via transformers and weakly supervised learning
Obtaining player identities is essential for analyzing the game and is used in downstream tasks such as game event recognition.
Optical Character Recognition
Optical Character Recognition (OCR)
+3
Player Tracking and Identification in Ice Hockey
The player identification model further takes advantage of the available NHL game roster data to obtain a player identification accuracy of 83%.
DeepDarts: Modeling Keypoints as Objects for Automatic Scorekeeping in Darts using a Single Camera
In the primary dataset containing 15k images captured from a face-on view of the dartboard using a smartphone, DeepDarts predicted the total score correctly in 94. 7% of the test images.
Event detection in coarsely annotated sports videos via parallel multi receptive field 1D convolutions
Experimental results demonstrate the effectiveness of the network by obtaining a 55% average F1 score on the NHL dataset and by achieving competitive performance compared to the state of the art on the SoccerNet dataset.
Ranked #4 on
Action Spotting
on SoccerNet
