10 citations · 17 across the 4 of their papers we have counts for
4 papers
Action tube generation by person query matching for spatio-temporal action detection
Kazuki Omi, Jion Oshima, Toru Tamaki
This paper proposes a method for spatio-temporal action detection (STAD) that directly generates action tubes from the original video without relying on post-processing steps such…
Query matching for spatio-temporal action detection with query-based object detector
Shimon Hori, Kazuki Omi, Toru Tamaki
In this paper, we propose a method that extends the query-based object detection model, DETR, to spatio-temporal action detection, which requires maintaining temporal consistency i…
Performance Evaluation of Action Recognition Models on Low Quality Videos
Aoi Otani, Ryota Hashiguchi, Kazuki Omi +2
In the design of action recognition models, the quality of videos is an important issue; however, the trade-off between the quality and performance is often ignored. In general, ac…
Model-agnostic Multi-Domain Learning with Domain-Specific Adapters for Action Recognition
Kazuki Omi, Jun Kimata, Toru Tamaki
In this paper, we propose a multi-domain learning model for action recognition. The proposed method inserts domain-specific adapters between layers of domain-independent layers of…