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Found 8 papers, 3 papers with code
eMotions: A Large-Scale Dataset for Emotion Recognition in Short Videos
The prevailing use of SVs to spread emotions leads to the necessity of emotion recognition in SVs.
Affective Video Content Analysis: Decade Review and New Perspectives
In this study, we comprehensively review the development of AVCA over the past decade, particularly focusing on the most advanced methods adopted to address the three major challenges of video feature extraction, expression subjectivity, and multimodal feature fusion.
Cross-modal information fusion for voice spoofing detection
Researchers have proposed many methods to defend against these attacks, but in the existing methods, researchers just focus on speech features.
Ranked #1 on
Voice Anti-spoofing
on ASVspoof 2019 - PA
Physiological-Physical Feature Fusion for Automatic Voice Spoofing Detection
This method involves feature extraction, a densely connected convolutional neural network with squeeze and excitation block (SE-DenseNet), multi-scale residual neural network with squeeze and excitation block (SE-Res2Net) and feature fusion strategies.
Multi-Agent Path Planning based on MPC and DDPG
The problem of mixed static and dynamic obstacle avoidance is essential for path planning in highly dynamic environment.
Agent-Based Campus Novel Coronavirus Infection and Control Simulation
Corona Virus Disease 2019 (COVID-19), due to its extremely high infectivity, has been spreading rapidly around the world and bringing huge influence to socioeconomic development as well as people's daily life.
Social and Information Networks Physics and Society Populations and Evolution
Multi-scale discriminative Region Discovery for Weakly-Supervised Object Localization
On ILSVRC 2016, the proposed method yields the Top-1 localization error of 48. 65\%, which outperforms previous results by 2. 75\%.
Representation Learning with Deconvolution for Multivariate Time Series Classification and Visualization
We propose a new model based on the deconvolutional networks and SAX discretization to learn the representation for multivariate time series.
