4 citations · 5 across the 5 of their papers we have counts for
6 papers
Graph Contrastive Learning with Implicit Augmentations
Huidong Liang, Xingjian Du, Bilei Zhu +3
Existing graph contrastive learning methods rely on augmentation techniques based on random perturbations (e.g., randomly adding or dropping edges and nodes). Nevertheless, alterin…
HTS-AT: A Hierarchical Token-Semantic Audio Transformer for Sound Classification and Detection
Ke Chen, Xingjian Du, Bilei Zhu +3
Audio classification is an important task of mapping audio samples into their corresponding labels. Recently, the transformer model with self-attention mechanisms has been adopted…
Attention-based cross-modal fusion for audio-visual voice activity detection in musical video streams
Yuanbo Hou, Zhesong Yu, Xia Liang +4
Many previous audio-visual voice-related works focus on speech, ignoring the singing voice in the growing number of musical video streams on the Internet. For processing diverse mu…
Rule-embedded network for audio-visual voice activity detection in live musical video streams
Yuanbo Hou, Yi Deng, Bilei Zhu +2
Detecting anchor's voice in live musical streams is an important preprocessing for music and speech signal processing. Existing approaches to voice activity detection (VAD) primari…
Contrastive Unsupervised Learning for Audio Fingerprinting
Zhesong Yu, Xingjian Du, Bilei Zhu +1
The rise of video-sharing platforms has attracted more and more people to shoot videos and upload them to the Internet. These videos mostly contain a carefully-edited background au…
ByteCover: Cover Song Identification via Multi-Loss Training
Xingjian Du, Zhesong Yu, Bilei Zhu +2
We present in this paper ByteCover, which is a new feature learning method for cover song identification (CSI). ByteCover is built based on the classical ResNet model, and two majo…