Young Hwi Kim — accepted AI-conference papers

2022

A Sliding Window Scheme for Online Temporal Action Localization

Young Hwi Kim, Hyolim Kang, Seon Joo Kim

ECCV 2022poster

"Most online video understanding tasks aim to immediately process each streaming frame and output predictions frame-by-frame. For extension to instance-level predictions of existing online video tasks, Online Temporal Action Localization (On-TAL) has been recently proposed. However, simple On-TAL ap…

Cited by 11 Source ↗PDF ↗Scholar ↗

2018

Teaching Machines to Understand Baseball Games: Large-Scale Baseball Video Database for Multiple Video Understanding Tasks

Minho Shim, Young Hwi Kim, Kyungmin Kim, Seon Joo Kim

ECCV 2018poster

A major obstacle in teaching machines to understand videos is the lack of training data, as creating temporal annotations for long videos requires a huge amount of human effort. To this end, we introduce a new large-scale baseball video dataset called the BBDB, which is produced semi-automatically b…

Cited by 16 Source ↗PDF ↗Scholar ↗