Explanipedia

A secreted glycoside hydrolase of Puccinia triticina modulates fungal pathogenesis and host immunity Open

Yanan Lu, Mengting Li, Shanshan Zhao, Yanhui Zhang, Na Liu , et al. · 2025

NaME: A Natural Micro-expression Dataset for Micro-expression Recognition in the Wild Open

Jiateng Liu, Hengcan Shi, Haiwen Liang, Xiaolin Xu, Yuan Zong , et al. · 2025

Visual-like Template Diffusion: Boosting Single-Sequence Protein Structure Prediction by Adapting Image Diffusion Models Open

Zhen Cui, Xudong Wang, Tong Zhang, Xu Guo, Fuyun Wang , et al. · 2025

Single-sequence protein structure prediction has drawn increasing attention due to the high computational costs associated with obtaining homologous information. Here, we propose a visual-like template diffusion method, named TDFold, to ac…

Visual-like Template Diffusion: Boosting Single-Sequence Protein Structure Prediction by Adapting Image Diffusion Models Open

Xudong Wang, Tong Zhang, Zhen Cui, Xu Guo, Fuyun Wang , et al. · 2025

Single-sequence protein structure prediction has drawn increasing attention due to the high computational costs associated with obtaining homologous information. Here, we propose a visual-like template diffusion method, named TDFold, to ac…

Towards Federated Learning Driving Technology for Privacy-Preserving Micro-Expression Recognition Open

Mingpei Wang, Ling Zhou, Xiaohua Huang, Wenming Zheng · 2025

LightRoseTTA: High‐Efficient and Accurate Protein Structure Prediction Using a Light‐Weight Deep Graph Model Open

Xudong Wang, Tong Zhang, Guangbu Liu, Zhen Cui, Zhiyong Zeng , et al. · 2025

Accurately predicting protein structure, from sequences to 3D structures, is of great significance in biological research. To tackle this issue, a representative deep big model, RoseTTAFold, is proposed with promising success. Here, “a lig…

Decoupled Doubly Contrastive Learning for Cross-Domain Facial Action Unit Detection Open

Yong Li, Menglin Liu, Zhen Cui, Yi Ding, Yuan Zong , et al. · 2025

Despite the impressive performance of current vision-based facial action unit (AU) detection approaches, they are heavily susceptible to the variations across different domains and the cross-domain AU detection methods are under-explored. …

Multi-modal Speech Emotion Recognition via Feature Distribution Adaptation Network Open

Shaokai Li, Yixuan Ji, Peng Song, Haoqin Sun, Wenming Zheng · 2024

In this paper, we propose a novel deep inductive transfer learning framework, named feature distribution adaptation network, to tackle the challenging multi-modal speech emotion recognition problem. Our method aims to use deep transfer lea…

A Survey of Deep Learning for Group-level Emotion Recognition Open

Xiaohua Huang, Jinke Xu, Wenming Zheng, Qirong Mao, Abhinav Dhall · 2024

With the advancement of artificial intelligence (AI) technology, group-level emotion recognition (GER) has emerged as an important area in analyzing human behavior. Early GER methods are primarily relied on handcrafted features. However, w…

Towards Realistic Emotional Voice Conversion using Controllable Emotional Intensity Open

Tianhua Qi, Shiyan Wang, Xinlu Cheng, Yan Zhao, Yuan Zong , et al. · 2024

Realistic emotional voice conversion (EVC) aims to enhance emotional diversity of converted audios, making the synthesized voices more authentic and natural. To this end, we propose Emotional Intensity-aware Network (EINet), dynamically ad…

Temporal Label Hierachical Network for Compound Emotion Recognition Open

Sunan Li, Hailun Lian, Cheng Lu, Yan Zhao, Tianhua Qi , et al. · 2024

The emotion recognition has attracted more attention in recent decades. Although significant progress has been made in the recognition technology of the seven basic emotions, existing methods are still hard to tackle compound emotion recog…

PAVITS: Exploring Prosody-aware VITS for End-to-End Emotional Voice Conversion Open

Tianhua Qi, Wenming Zheng, Cheng Lu, Yuan Zong, Hailun Lian · 2024

In this paper, we propose Prosody-aware VITS (PAVITS) for emotional voice conversion (EVC), aiming to achieve two major objectives of EVC: high content naturalness and high emotional naturalness, which are crucial for meeting the demands o…

Emotion-Aware Contrastive Adaptation Network for Source-Free Cross-Corpus Speech Emotion Recognition Open

Yan Zhao, Jincen Wang, Cheng Lu, Sunan Li, Björn W. Schuller , et al. · 2024

Cross-corpus speech emotion recognition (SER) aims to transfer emotional knowledge from a labeled source corpus to an unlabeled corpus. However, prior methods require access to source data during adaptation, which is unattainable in real-l…

Speech Swin-Transformer: Exploring a Hierarchical Transformer with Shifted Windows for Speech Emotion Recognition Open

Yong Wang, Cheng Lu, Hailun Lian, Yan Zhao, Björn W. Schuller , et al. · 2024

Swin-Transformer has demonstrated remarkable success in computer vision by leveraging its hierarchical feature representation based on Transformer. In speech signals, emotional information is distributed across different scales of speech f…

Improving Speaker-independent Speech Emotion Recognition Using Dynamic Joint Distribution Adaptation Open

Cheng Lu, Yuan Zong, Hailun Lian, Yan Zhao, Björn W. Schuller , et al. · 2024

In speaker-independent speech emotion recognition, the training and testing samples are collected from diverse speakers, leading to a multi-domain shift challenge across the feature distributions of data from different speakers. Consequent…

Shared Latent Embedding Learning for Multi-View Subspace Clustering Open

Liu Zhao-hu, Peng Song, Jinshuai Mu, Wenming Zheng · 2023

Most existing multi-view subspace clustering approaches only capture the inter-view similarities between different views and ignore the optimal local geometric structure of the original data. To this end, in this letter, we put forward a n…

Towards Domain-Specific Cross-Corpus Speech Emotion Recognition Approach Open

Yan Zhao, Yuan Zong, Hailun Lian, Cheng Lu, Jingang Shi , et al. · 2023

Cross-corpus speech emotion recognition (SER) poses a challenge due to feature distribution mismatch, potentially degrading the performance of established SER methods. In this paper, we tackle this challenge by proposing a novel transfer s…

LightRoseTTA: High-efficient and Accurate Protein Structure Prediction Using an Ultra-Lightweight Deep Graph Model Open

Xudong Wang, Tong Zhang, Guangbu Liu, Zhen Cui, Zhiyong Zeng , et al. · 2023

Accurately predicting protein structure, from amino acid sequences to three-dimensional structures, is of great significance in biological research. To tackle this issue, a representative deep big model, RoseTTAFold, has been proposed with…

An Empirical Study of Super-resolution on Low-resolution Micro-expression Recognition Open

Ling Zhou, Mingpei Wang, Xiaohua Huang, Wenming Zheng, Qirong Mao , et al. · 2023

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. Despite considerable advancements in super-…

Layer-Adapted Implicit Distribution Alignment Networks for Cross-Corpus Speech Emotion Recognition Open

Yan Zhao, Yuan Zong, Jincen Wang, Hailun Lian, Cheng Lu , et al. · 2023

In this paper, we propose a new unsupervised domain adaptation (DA) method called layer-adapted implicit distribution alignment networks (LIDAN) to address the challenge of cross-corpus speech emotion recognition (SER). LIDAN extends our p…

Towards A Robust Group-level Emotion Recognition via Uncertainty-Aware Learning Open

Qing Zhu, Qirong Mao, Jialin Zhang, Xiaohua Huang, Wenming Zheng · 2023

Group-level emotion recognition (GER) is an inseparable part of human behavior analysis, aiming to recognize an overall emotion in a multi-person scene. However, the existing methods are devoted to combing diverse emotion cues while ignori…

EEG-based Emotion Style Transfer Network for Cross-dataset Emotion Recognition Open

Yijin Zhou, Fu Li, Yang Li, Youshuo Ji, Lijian Zhang , et al. · 2023

As the key to realizing aBCIs, EEG emotion recognition has been widely studied by many researchers. Previous methods have performed well for intra-subject EEG emotion recognition. However, the style mismatch between source domain (training…

Window-Adjusted Common Spatial Pattern for Detecting Error-Related Potentials in P300 BCI Open

Zhihua Huang, Minghong Li, Wenming Zheng, Yingjie Wu, Kun Jiang , et al. · 2023

Under certain task conditions, error-related potential (ErrP) will be elicited, meaning that the subject is perceiving an error, responding to an external error, or engaging in a cognitive process of reinforcement learning. The detection o…

CMNet: Contrastive Magnification Network for Micro-Expression Recognition Open

Mengting Wei, Xingxun Jiang, Wenming Zheng, Yuan Zong, Cheng Lu , et al. · 2023

Micro-Expression Recognition (MER) is challenging because the Micro-Expressions' (ME) motion is too weak to distinguish. This hurdle can be tackled by enhancing intensity for a more accurate acquisition of movements. However, existing magn…

Learning Local to Global Feature Aggregation for Speech Emotion Recognition Open

Cheng Lu, Hailun Lian, Wenming Zheng, Yuan Zong, Yan Zhao , et al. · 2023

Transformer has emerged in speech emotion recognition (SER) at present. However, its equal patch division not only damages frequency information but also ignores local emotion correlations across frames, which are key cues to represent emo…

Cross Domain Correlation Maximization for Enhancing the Target Recognition of SSVEP-Based Brain–Computer Interfaces Open

Wenli Lan, Ruimin Wang, Yikang He, Yuan Zong, Yue Leng , et al. · 2023

The target recognition performance of steady-state visual evoked potential (SSVEP)-based brain-computer interfaces can be significantly improved with a training-based approach. However, the training procedure is time consuming and often ca…

A novel Adaptive Weighted Transfer Subspace Learning Method for Cross-Database Speech Emotion Recognition Open

Keke Zhao, Peng Song, Shaokai Li, Wenjing Zhang, Wenming Zheng · 2022

In this letter, we present an adaptive weighted transfer subspace learning (AWTSL) method for cross-database speech emotion recognition (SER), which can efficiently eliminate the discrepancy between source and target databases. Specificall…

Depression Assessment Method: An EEG Emotion Recognition Framework Based on Spatiotemporal Neural Network Open

Hongli Chang, Yuan Zong, Wenming Zheng, Chuangao Tang, Jie Zhu , et al. · 2022

The main characteristic of depression is emotional dysfunction, manifested by increased levels of negative emotions and decreased levels of positive emotions. Therefore, accurate emotion recognition is an effective way to assess depression…

A Calibration-free Approach to Implementing P300-based Brain–computer Interface Open

Zhihua Huang, Jiannan Guo, Wenming Zheng, Yingjie Wu, Zhixiong Lin , et al. · 2022

A Novel Transferable Sparse Regression Method for Cross-Database Facial Expression Recognition Open

Wenjing Zhang, Peng Song, Wenming Zheng · 2021

In this letter, we propose a novel transferable sparse regression (TSR) method, for cross-database facial expression recognition (FER). In TSR, we firstly present a novel regression function to regress the data into a latent representation…

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