activity
20162024
most citedDehazeNet: An End-to-End System for Single Image Haze Removal

3.4k citations · 3.7k across the 22 of their papers we have counts for

collaborators

22 papers

eess.AS2024

Multi-Scale Temporal Transformer For Speech Emotion Recognition

Zhipeng Li, Xiaofen Xing, Yuanbo Fang +3

Speech emotion recognition plays a crucial role in human-machine interaction systems. Recently various optimized Transformers have been successfully applied to speech emotion recog…

cs.CV2023★ 1 cited

LAPP: Layer Adaptive Progressive Pruning for Compressing CNNs from Scratch

Pucheng Zhai, Kailing Guo, Fang Liu +2

Structured pruning is a commonly used convolutional neural network (CNN) compression approach. Pruning rate setting is a fundamental problem in structured pruning. Most existing wo…

cs.SD2023★ 3 cited

Vesper: A Compact and Effective Pretrained Model for Speech Emotion Recognition

Weidong Chen, Xiaofen Xing, Peihao Chen +1

This paper presents a paradigm that adapts general large-scale pretrained models (PTMs) to speech emotion recognition task. Although PTMs shed new light on artificial general intel…

cs.SD2023★ 1 cited

DWFormer: Dynamic Window transFormer for Speech Emotion Recognition

Shuaiqi Chen, Xiaofen Xing, Weibin Zhang +2

Speech emotion recognition is crucial to human-computer interaction. The temporal regions that represent different emotions scatter in different parts of the speech locally. Moreov…

eess.AS2023★ 90 cited

SpeechFormer++: A Hierarchical Efficient Framework for Paralinguistic Speech Processing

Weidong Chen, Xiaofen Xing, Xiangmin Xu +2

Paralinguistic speech processing is important in addressing many issues, such as sentiment and neurocognitive disorder analyses. Recently, Transformer has achieved remarkable succe…

cs.SD2023★ 2 cited

DST: Deformable Speech Transformer for Emotion Recognition

Weidong Chen, Xiaofen Xing, Xiangmin Xu +2

Enabled by multi-head self-attention, Transformer has exhibited remarkable results in speech emotion recognition (SER). Compared to the original full attention mechanism, window-ba…

cs.CV2022★ 7 cited

Superpoint Transformer for 3D Scene Instance Segmentation

Jiahao Sun, Chunmei Qing, Junpeng Tan +1

Most existing methods realize 3D instance segmentation by extending those models used for 3D object detection or 3D semantic segmentation. However, these non-straightforward method…

cs.CV2022

Context Sensing Attention Network for Video-based Person Re-identification

Kan Wang, Changxing Ding, Jianxin Pang +1

Video-based person re-identification (ReID) is challenging due to the presence of various interferences in video frames. Recent approaches handle this problem using temporal aggreg…

cs.CL2022★ 3 cited

CPED: A Large-Scale Chinese Personalized and Emotional Dialogue Dataset for Conversational AI

Yirong Chen, Weiquan Fan, Xiaofen Xing +5

Human language expression is based on the subjective construal of the situation instead of the objective truth conditions, which means that speakers' personalities and emotions aft…

cs.CV2022★ 1 cited

Compact Model Training by Low-Rank Projection with Energy Transfer

Kailing Guo, Zhenquan Lin, Canyang Chen +3

Low-rankness plays an important role in traditional machine learning, but is not so popular in deep learning. Most previous low-rank network compression methods compress networks b…

cs.SD2022

SpeechFormer: A Hierarchical Efficient Framework Incorporating the Characteristics of Speech

Weidong Chen, Xiaofen Xing, Xiangmin Xu +2

Transformer has obtained promising results on cognitive speech signal processing field, which is of interest in various applications ranging from emotion to neurocognitive disorder…

cs.CV2021

Weight Evolution: Improving Deep Neural Networks Training through Evolving Inferior Weight Values

Zhenquan Lin, Kailing Guo, Xiaofen Xing +1

To obtain good performance, convolutional neural networks are usually over-parameterized. This phenomenon has stimulated two interesting topics: pruning the unimportant weights for…

cs.SD2021★ 74 cited

Key-Sparse Transformer for Multimodal Speech Emotion Recognition

Weidong Chen, Xiaofeng Xing, Xiangmin Xu +2

Speech emotion recognition is a challenging research topic that plays a critical role in human-computer interaction. Multimodal inputs further improve the performance as more emoti…

cs.SD2021★ 1 cited

LSSED: a large-scale dataset and benchmark for speech emotion recognition

Weiquan Fan, Xiangmin Xu, Xiaofen Xing +2

Speech emotion recognition is a vital contributor to the next generation of human-computer interaction (HCI). However, current existing small-scale databases have limited the devel…

cs.CV2019★ 20 cited

Listwise View Ranking for Image Cropping

Weirui Lu, Xiaofen Xing, Bolun Cai +1

Rank-based Learning with deep neural network has been widely used for image cropping. However, the performance of ranking-based methods is often poor and this is mainly due to two…

cs.CV2019★ 47 cited

BIT: Biologically Inspired Tracker

Bolun Cai, Xiangmin Xu, Xiaofen Xing +3

Visual tracking is challenging due to image variations caused by various factors, such as object deformation, scale change, illumination change and occlusion. Given the superior tr…

cs.CV2017

Deep Sampling Networks

Bolun Cai, Xiangmin Xu, Kailing Guo +2

Deep convolutional neural networks achieve excellent image up-sampling performance. However, CNN-based methods tend to restore high-resolution results highly depending on tradition…

cs.CV2017★ 3 cited

Manifold Regularized Slow Feature Analysis for Dynamic Texture Recognition

Jie Miao, Xiangmin Xu, Xiaofen Xing +1

Dynamic textures exist in various forms, e.g., fire, smoke, and traffic jams, but recognizing dynamic texture is challenging due to the complex temporal variations. In this paper,…

cs.CV2017★ 6 cited

Single Image Super-Resolution Using Multi-Scale Convolutional Neural Network

Xiaoyi Jia, Xiangmin Xu, Bolun Cai +1

Methods based on convolutional neural network (CNN) have demonstrated tremendous improvements on single image super-resolution. However, the previous methods mainly restore images…

cs.CV2017★ 22 cited

Multi-scale Convolutional Neural Networks for Crowd Counting

Lingke Zeng, Xiangmin Xu, Bolun Cai +2

Crowd counting on static images is a challenging problem due to scale variations. Recently deep neural networks have been shown to be effective in this task. However, existing neur…

cs.CV2016★ 3 cited

Improving training of deep neural networks via Singular Value Bounding

Kui Jia

Deep learning methods achieve great success recently on many computer vision problems, with image classification and object detection as the prominent examples. In spite of these p…

cs.CV2016★ 3.4k cited

DehazeNet: An End-to-End System for Single Image Haze Removal

Bolun Cai, Xiangmin Xu, Kui Jia +2

Single image haze removal is a challenging ill-posed problem. Existing methods use various constraints/priors to get plausible dehazing solutions. The key to achieve haze removal i…