8 citations · 8 across the 3 of their papers we have counts for
3 papers
cs.CV2024
Fine-grained length controllable video captioning with ordinal embeddings
Tomoya Nitta, Takumi Fukuzawa, Toru Tamaki
This paper proposes a method for video captioning that controls the length of generated captions. Previous work on length control often had few levels for expressing length. In thi…
cs.CV2022
Object-ABN: Learning to Generate Sharp Attention Maps for Action Recognition
Tomoya Nitta, Tsubasa Hirakawa, Hironobu Fujiyoshi +1
In this paper we propose an extension of the Attention Branch Network (ABN) by using instance segmentation for generating sharper attention maps for action recognition. Methods for…
cs.CV2022★ 8 cited
ObjectMix: Data Augmentation by Copy-Pasting Objects in Videos for Action Recognition
Jun Kimata, Tomoya Nitta, Toru Tamaki
In this paper, we propose a data augmentation method for action recognition using instance segmentation. Although many data augmentation methods have been proposed for image recogn…