Sports Ball Detection and Tracking
5 papers with code • 5 benchmarks • 5 datasets
detect a (x, y)-coordinate of ball location from each image in a given sports video clip.
Benchmarks
These leaderboards are used to track progress in Sports Ball Detection and Tracking
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Volleyball
Soccer
Most implemented papers
DeepBall: Deep Neural-Network Ball Detector
nttcom/wasb-sbdt
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The paper describes a deep network based object detector specialized for ball detection in long shot videos.
Real-time CNN-based Segmentation Architecture for Ball Detection in a Single View Setup
nttcom/wasb-sbdt
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This paper considers the task of detecting the ball from a single viewpoint in the challenging but common case where the ball interacts frequently with players while being poorly contrasted with respect to the background.
TrackNetV2: Efficient Shuttlecock Tracking Network
nttcom/wasb-sbdt
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Conference 2020
In this work, TrackNetV2 is proposed to improve the performance of TrackNet from various aspects, especially processing speed, prediction accuracy, and GPU memory usage.
MonoTrack: Shuttle trajectory reconstruction from monocular badminton video
nttcom/wasb-sbdt
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Trajectory estimation is a fundamental component of racket sport analytics, as the trajectory contains information not only about the winning and losing of each point, but also how it was won or lost.
Widely Applicable Strong Baseline for Sports Ball Detection and Tracking
nttcom/wasb-sbdt
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Experimental results demonstrate that our approach is substantially superior to existing methods on all the sports categories covered by the datasets.
