L
Ling Zhou
Researcher at Jiangsu University
Publications - 5
Citations - 44
Ling Zhou is an academic researcher from Jiangsu University. The author has contributed to research in topics: Feature learning & Feature (machine learning). The author has an hindex of 2, co-authored 5 publications receiving 9 citations.
Papers
More filters
Journal ArticleDOI
A survey of micro-expression recognition
Ling Zhou,Xiuyan Shao,Qirong Mao +2 more
TL;DR: A comprehensive survey on micro-expression recognition, including datasets and algorithms that provide insights into these intrinsic problems, is provided, including the available datasets that are widely used in the literature.
Journal ArticleDOI
Feature refinement: An expression-specific feature learning and fusion method for micro-expression recognition
TL;DR: Wang et al. as mentioned in this paper proposed Feature Refinement (FeatRef) with expression-specific feature learning and fusion for micro-expression recognition that aims to obtain salient and discriminative features for specific expressions and predicts expressions by fusing expression specific features.
Posted Content
Objective Class-based Micro-Expression Recognition through Simultaneous Action Unit Detection and Feature Aggregation.
Ling Zhou,Qirong Mao,Ming Dong +2 more
TL;DR: Zhang et al. as discussed by the authors proposed a novel deep neural network model for objective class-based micro-expression recognition, which simultaneously detects AUs and aggregates AU-level features into micro-expression-level representation through Graph Convolutional Networks (GCN).
Posted Content
Feature refinement: An expression-specific feature learning and fusion method for micro-expression recognition
TL;DR: Wang et al. as mentioned in this paper proposed Feature Refinement (FR) with expression-specific feature learning and fusion for micro-expression recognition, which aims to obtain salient and discriminative features for specific expressions and also predict expression by fusing the expressionspecific features.
Posted Content
Region attention and graph embedding network for occlusion objective class-based micro-expression recognition.
TL;DR: Wang et al. as mentioned in this paper proposed a Region-Inspired (RI) module and Relation Reasoning (RR) module to suppress the influence of occlusion in micro-expression recognition.