Corpus ID: 237485612

FineAction: A Fine-Grained Video Dataset for Temporal Action Localization

@inproceedings{Liu2021FineActionAF,
  title={FineAction: A Fine-Grained Video Dataset for Temporal Action Localization},
  author={Yi Liu and Limin Wang and Xiao Ma and Yali Wang and Yu Qiao},
  year={2021}
}
  • Yi Liu, Limin Wang, +2 authors Yu Qiao
  • Published 2021
  • Computer Science
Temporal action localization (TAL) is an important and challenging problem in video understanding. However, most existing TAL benchmarks are built upon the coarse granularity of action classes, which exhibits two major limitations in this task. First, coarse-level actions can make the localization models overfit in high-level context information, and ignore the atomic action details in the video. Second, the coarse action classes often lead to the ambiguous annotations of temporal boundaries… Expand

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References

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