4 citations · 11 across the 7 of their papers we have counts for
7 papers
Don't worry about mistakes! Glass Segmentation Network via Mistake Correction
Chengyu Zheng, Peng Li, Xiao-Ping Zhang +2
Recall one time when we were in an unfamiliar mall. We might mistakenly think that there exists or does not exist a piece of glass in front of us. Such mistakes will remind us to w…
Time-Variance Aware Real-Time Speech Enhancement
Chengyu Zheng, Yuan Zhou, Xiulian Peng +2
Time-variant factors often occur in real-world full-duplex communication applications. Some of them are caused by the complex environment such as non-stationary environmental noise…
Real-time speech enhancement with dynamic attention span
Chengyu Zheng, Yuan Zhou, Xiulian Peng +2
For real-time speech enhancement (SE) including noise suppression, dereverberation and acoustic echo cancellation, the time-variance of the audio signals becomes a severe challenge…
Scale-Semantic Joint Decoupling Network for Image-text Retrieval in Remote Sensing
Chengyu Zheng, Ning song, Ruoyu Zhang +3
Image-text retrieval in remote sensing aims to provide flexible information for data analysis and application. In recent years, state-of-the-art methods are dedicated to ``scale de…
End-to-End Neural Speech Coding for Real-Time Communications
Xue Jiang, Xiulian Peng, Chengyu Zheng +3
Deep-learning based methods have shown their advantages in audio coding over traditional ones but limited attention has been paid on real-time communications (RTC). This paper prop…
GlassNet: Label Decoupling-based Three-stream Neural Network for Robust Image Glass Detection
C. Zheng, D. Shi, X. Yan +5
Most of the existing object detection methods generate poor glass detection results, due to the fact that the transparent glass shares the same appearance with arbitrary objects be…
Interactive Speech and Noise Modeling for Speech Enhancement
Chengyu Zheng, Xiulian Peng, Yuan Zhang +2
Speech enhancement is challenging because of the diversity of background noise types. Most of the existing methods are focused on modelling the speech rather than the noise. In thi…