arrow
返回

Sparse Action Tube Detection

delete2024-01-01
delete0
PRE
AI
Y
Yixuan Li
Z
Zhenzhi Wang
Z
Zhifeng Li
Limin Wang 封面图
Limin Wang (Limin Wang) *
DOI:10.1109/TIP.2024.3368958delete
delete原文链接
delete原文求助
delete分享
delete收藏
摘要

摘要

En 中文
Action tube detection is a challenging task as it requires not only to locate action instances in each frame, but also link them in time. Existing action tube detection methods often employ multi-stage pipelines with complex designs and time-consuming linking procedure. In this paper, we present a simple end-to-end action tube detection method, termed as Sparse Tube Detector (STDet). Unlike those dense action detectors, our core idea is to use a set of learnable tube queries and directly decode them into action tubes (i.e., a set of tracked boxes with action label) from video content. This sparse detection paradigm shares several advantages. First, the large number of hand-crafted anchor candidates in dense action detectors is greatly reduced to a small number of learnable tubes, which results in a more efficient detection framework. Second, our learnable tube queries directly attend the whole video content, which endows our method with the capacity of capturing long-range information for action detection. Finally, our action detector is an end-to-end tube detection without requiring the linking procedure, which directly and explicitly predicts the action boundary instead of depending on the linking strategy. Extensive experiments shows that our STDet outperforms the previous state-of-the-art methods on two challenging untrimmed video action detection datasets of UCF101-24 and MultiSports. We hope our method will be an simple end-to-end tube detection baseline and can inspire new ideas in this direction.
Keyword:
Electron tubes
Detectors
Feature extraction
Location awareness
Predictive models
Task analysis
Transformers
Spatio-temporal action detection
sparse action detector
action recognition

期刊

IEEE Transactions on Image Processing 封面图
IEEE Transactions on Image Processing
IF:
13.7
论文数:
1.0W
被引数:
8.4W

机构

N
nanjing university
学者数:
7.8W
论文数: 5.6W
被引数: 87
引用论文

引用论文

Diagnosis of Coeliac Disease in Children Younger Than 2 Years
err2013-02-01
err0
errOAAI
errZrinjka Mišak; Iva Hojsak; Oleg Jadrešin; Alemka Jaklin Kekez; Slaven Abdović; Sanja Kolaček
err分享
err收藏
Synthesis of n-type semiconducting diamond film using diphosphorus pentaoxide as the doping source以五氧化二磷为掺杂源合成n型半导体金刚石膜
err1990-10-01
err0
PREAI
errKen Okano; Hideo Kiyota; Tatsuya Iwasaki; Yoshitaka Nakamura; Yukio Akiba; Tateki Kurosu; Masamori Iida; Terutaro Nakamura
err分享
err收藏
学者 查看更多内容