Action recognition in still images using a multi-attention guided network with weakly supervised saliency detection

2021 ◽  
Author(s):  
Seyed Sajad Ashrafi ◽  
Shahriar B. Shokouhi ◽  
Ahmad Ayatollahi
Keyword(s):  
Action Recognition ◽  
Saliency Detection ◽  
Still Images ◽  
Weakly Supervised

A Unified Approach of Object-Level Saliency Detection in Images and Videos

2013 ◽  
Vol 765-767 ◽  
pp. 1401-1405
Author(s):  
Chi Zhang ◽  
Wei Qiang Wang
Keyword(s):  
Quality Evaluation ◽  
Saliency Detection ◽  
Visual Saliency ◽  
Unified Approach ◽  
Feature Maps ◽  
Still Images ◽  
Saliency Maps ◽  
Novel Method ◽  
Object Level ◽  
Important Branch

Object-level saliency detection is an important branch of visual saliency. In this paper, we propose a novel method which can conduct object-level saliency detection in both images and videos in a unified way. We employ a more effective spatial compactness assumption to measure saliency instead of the popular contrast assumption. In addition, we present a combination framework which integrates multiple saliency maps generated in different feature maps. The proposed algorithm can automatically select saliency maps of high quality according to the quality evaluation score we define. The experimental results demonstrate that the proposed method outperforms all state-of-the-art methods on both of the datasets of still images and video sequences.

Weakly-Supervised Multi-Person Action Recognition in 360° Videos

2020 ◽  
Author(s):  
Junnan Li ◽  
Jianquan Liu ◽  
Yongkang Wang ◽  
Shoji Nishimura ◽  
Mohan S. Kankanhalli
Keyword(s):  
Action Recognition ◽  
Weakly Supervised
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