7 citations · 36 across the 15 of their papers we have counts for
15 papers
Learnable Differencing Center for Nighttime Depth Perception
Zhiqiang Yan, Yupeng Zheng, Chongyi Li +2
Depth completion is the task of recovering dense depth maps from sparse ones, usually with the help of color images. Existing image-guided methods perform well on daytime depth per…
FedREP: A Byzantine-Robust, Communication-Efficient and Privacy-Preserving Framework for Federated Learning
Yi-Rui Yang, Kun Wang, Wu-Jun Li
Federated learning (FL) has recently become a hot research topic, in which Byzantine robustness, communication efficiency and privacy preservation are three important aspects. Howe…
Network Traffic Anomaly Detection Method Based on Multi scale Residual Feature
Xueyuan Duan, Yu Fu, Kun Wang
To address the problem that traditional network traffic anomaly detection algorithms do not suffi-ciently mine potential features in long time domain, an anomaly detection method b…
Pitch Preservation In Singing Voice Synthesis
Shujun Liu, Hai Zhu, Kun Wang +1
Suffering from limited singing voice corpus, existing singing voice synthesis (SVS) methods that build encoder-decoder neural networks to directly generate spectrogram could lead t…
Regularizing Nighttime Weirdness: Efficient Self-supervised Monocular Depth Estimation in the Dark
Kun Wang, Zhenyu Zhang, Zhiqiang Yan +4
Monocular depth estimation aims at predicting depth from a single image or video. Recently, self-supervised methods draw much attention since they are free of depth annotations and…
RigNet: Repetitive Image Guided Network for Depth Completion
Zhiqiang Yan, Kun Wang, Xiang Li +3
Depth completion deals with the problem of recovering dense depth maps from sparse ones, where color images are often used to facilitate this task. Recent approaches mainly focus o…