Spatial attention based visual semantic learning for action recognition in still images-Reference-Cited by-同舟云学术

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Spatial attention based visual semantic learning for action recognition in still images

Published:2020-11 Issue: Volume:413 Page:383-396
ISSN:0925-2312
Container-title:Neurocomputing
language:en
Short-container-title:Neurocomputing

Author:

Zheng Yunpeng,Zheng Xiangtao,Lu Xiaoqiang,Wu Siyuan

Funder

Innovation Capability Support Program of Shaanxi

Natural Science Basic Research Program of Shaanxi

Publisher

Elsevier BV

Subject

Artificial Intelligence,Cognitive Neuroscience,Computer Science Applications

Reference48 articles.

1. Exemplar-based image saliency and co-saliency detection;Huang;Neurocomputing,2020

2. Effective image restoration for semantic segmentation;Niu;Neurocomputing,2020

3. Bayesian capsule networks for 3d human pose estimation from single 2d images;Ramírez;Neurocomputing,2020

4. Host-parasite: Graph LSTM-in-LSTM for group activity recognition;Shu;IEEE Trans. Neural Networks Learn. Syst.,2020

5. Euler label consistent K-SVD for image classification and action recognition;Song;Neurocomputing,2018

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1. Multi Step Knowledge Distillation Framework For Action Recognition in Still Images;2024 20th CSI International Symposium on Artificial Intelligence and Signal Processing (AISP);2024-02-21

2. Patch excitation network for boxless action recognition in still images;The Visual Computer;2023-09-25

3. From detection to understanding: A survey on representation learning for human-object interaction;Neurocomputing;2023-07

4. DETECTION OF STUDENTS' CLASSROOM CONCENTRATION BASED ON COMPONENT ATTENTION;INT J INNOV COMPUT I;2023

5. Efficient Still Image Action Recognition by the Combination of Ensemble Learning and Knowledge Distillation;2023 9th International Conference on Web Research (ICWR);2023-05-03

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