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Found 15 papers, 0 papers with code
HABD: a houma alliance book ancient handwritten character recognition database
The Houma Alliance Book, one of history's earliest calligraphic examples, was unearthed in the 1970s.
A Survey of Deep Learning for Group-level Emotion Recognition
With the advancement of artificial intelligence (AI) technology, group-level emotion recognition (GER) has emerged as an important area in analyzing human behavior.
An Empirical Study of Super-resolution on Low-resolution Micro-expression Recognition
Micro-expression recognition (MER) in low-resolution (LR) scenarios presents an important and complex challenge, particularly for practical applications such as group MER in crowded environments.
Towards A Robust Group-level Emotion Recognition via Uncertainty-Aware Learning
Group-level emotion recognition (GER) is an inseparable part of human behavior analysis, aiming to recognize an overall emotion in a multi-person scene.
EMC2A-Net: An Efficient Multibranch Cross-channel Attention Network for SAR Target Classification
In recent years, convolutional neural networks (CNNs) have shown great potential in synthetic aperture radar (SAR) target recognition.
A new database of Houma Alliance Book ancient handwritten characters and classifier fusion approach
This paper proposes a new database of Houma Alliance Book ancient handwritten characters and a multi-modal fusion method to recognize ancient handwritten characters.
Region attention and graph embedding network for occlusion objective class-based micro-expression recognition
More specifically, the backbone network aims at extracting feature representations from different facial regions, RI module computing an adaptive weight from the region itself based on attention mechanism with respect to the unobstructedness and importance for suppressing the influence of occlusion, and RR module exploiting the progressive interactions among these regions by performing graph convolutions.
Feature refinement: An expression-specific feature learning and fusion method for micro-expression recognition
It aims to obtain salient and discriminative features for specific expressions and also predict expression by fusing the expression-specific features.
Micro Expression Recognition
Micro-Expression Recognition
+1
Micro-expression Action Unit Detection with Spatio-temporal Adaptive Pooling
In this paper, we focus on AU detection in micro-expressions.
Learning a Target Sample Re-Generator for Cross-Database Micro-Expression Recognition
In this paper, we investigate the cross-database micro-expression recognition problem, where the training and testing samples are from two different micro-expression databases.
Analyzing the group sparsity based on the rank minimization methods
Then, we prove that group-based sparse coding is equivalent to the rank minimization problem, and thus the sparse coefficient of each group is measured by estimating the singular values of each group.
Analyzing the Affect of a Group of People Using Multi-modal Framework
We fuse face, upperbody and scene information for robustness of GER against the challenging environments.
Image denoising via group sparsity residual constraint
Group sparsity has shown great potential in various low-level vision tasks (e. g, image denoising, deblurring and inpainting).
Spontaneous Facial Micro-Expression Recognition using Discriminative Spatiotemporal Local Binary Pattern with an Improved Integral Projection
For increasing the discrimination of micro-expressions, we propose a new feature selection based on Laplacian method to extract the discriminative information for facial micro-expression recognition.
Towards Reading Hidden Emotions: A comparative Study of Spontaneous Micro-expression Spotting and Recognition Methods
For ME recognition, the performance of previous studies is low.
