Datasets:
Languages:
English
Size:
10K<n<100K
ArXiv:
Tags:
sports-analytics
computer-vision
object-tracking
trajectory-prediction
ball-tracking
racket-pose-estimation
License:
Upload README.md with huggingface_hub
Browse files
README.md
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[](https://github.com/OrcustD/RacketVision/)
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[](https://huggingface.co/datasets/linfeng302/RacketVision)
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[](https://huggingface.co/linfeng302/RacketVision-Models)
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[](https://github.com/OrcustD/RacketVision/blob/main/LICENSE)
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**RacketVision** is a large-scale, multi-sport dataset and benchmark for advancing computer vision in sports analytics, covering **badminton**, **table tennis**, and **tennis**. It is the first dataset to provide large-scale, fine-grained annotations for racket pose alongside traditional ball positions, enabling research into complex human-object interactions. The benchmark tackles three interconnected tasks: fine-grained **ball tracking**, articulated **racket pose estimation**, and predictive ball **trajectory forecasting**.
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- **Paper:** [arXiv:2511.17045](https://arxiv.org/abs/2511.17045)
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- **Code:** [github.com/OrcustD/RacketVision](https://github.com/OrcustD/RacketVision/)
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## Using this Hub repository
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[](https://github.com/OrcustD/RacketVision/)
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[](https://huggingface.co/datasets/linfeng302/RacketVision)
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[](https://huggingface.co/linfeng302/RacketVision-Models)
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**RacketVision** is a large-scale, multi-sport dataset and benchmark for advancing computer vision in sports analytics, covering **badminton**, **table tennis**, and **tennis**. It is the first dataset to provide large-scale, fine-grained annotations for racket pose alongside traditional ball positions, enabling research into complex human-object interactions. The benchmark tackles three interconnected tasks: fine-grained **ball tracking**, articulated **racket pose estimation**, and predictive ball **trajectory forecasting**.
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## Using this Hub repository
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