Group contextualization for video recognition
Learning discriminative representation from the complex spatio-temporal dynamic space is essential for video recognition. On top of those stylized spatio-temporal computational units, further refining the learnt feature with axial contexts is demonstrated to be promising in achieving this goal. Howe...
Saved in:
Main Authors: | HAO, Yanbin, ZHANG, Hao, NGO, Chong-wah, HE, Xiangnan |
---|---|
Format: | text |
Language: | English |
Published: |
Institutional Knowledge at Singapore Management University
2022
|
Subjects: | |
Online Access: | https://ink.library.smu.edu.sg/sis_research/7504 https://ink.library.smu.edu.sg/context/sis_research/article/8507/viewcontent/Hao_Group_Contextualization_for_Video_Recognition_CVPR_2022_paper.pdf |
Tags: |
Add Tag
No Tags, Be the first to tag this record!
|
Institution: | Singapore Management University |
Language: | English |
Similar Items
-
Meta-Transfer Learning for Few-Shot Learning
by: Qianru Sun, et al.
Published: (2020) -
Deep-based ingredient recognition for cooking recipe retrieval
by: CHEN, Jingjing, et al.
Published: (2016) -
Exploring object relation in mean teacher for cross-domain detection
by: CAI, Qi, et al.
Published: (2019) -
Person-level action recognition in complex events via TSD-TSM networks
by: HAO, Yanbin, et al.
Published: (2020) -
R2GAN: Cross-modal recipe retrieval with generative adversarial network
by: ZHU, Bin, et al.
Published: (2019)