A CRNN-GCN Piano Transcription Model Based On Audio And Skeleton Features-Reference-Cited by-同舟云学术

A CRNN-GCN Piano Transcription Model Based On Audio And Skeleton Features

Published:2023-06-04 Issue: Volume: Page:
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Container-title:2023 IEEE International Conference on Acoustics, Speech, and Signal Processing Workshops (ICASSPW)
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Author:

Li Yuqing¹,Wang Xianke¹,Wu Ruimin¹,Xu Wei¹,Chen Wenqing¹

Affiliation:

1. Huazhong University of Science and Technology,School of Electronic Information and Communications Hubei Provincial Key Laboratory of Smart Internet Technology,Wuhan,China,430074

Funder

National Natural Science Foundation of China

Publisher

IEEE

Link

http://xplorestaging.ieee.org/ielx7/10192576/10192577/10193618.pdf?arnumber=10193618

Reference18 articles.

1. Music gesture for visual sound separation;zhao;In IEEE/CVF Conference on Computer Vision and Pattern Recognition (CVPR),2020

2. Sia-gcn: A spatial information aware graph neural network with 2d convolutions for hand pose estimation;kong;In British Machine Vision Conference,2020

3. Semi-supervised classification with graph convolutional networks;welling;International Conference of Learning Representations (ICLR) 2017,2016

4. Spatial Temporal Graph Convolutional Networks for Skeleton-Based Action Recognition

5. Observing Pianist Accuracy and Form with Computer Vision

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1. CNN-Transformer Ensemble: Advancing Visual Piano Transcription with Global and Local Features;2024 International Joint Conference on Neural Networks (IJCNN);2024-06-30

2. A Two-Stage Audio-Visual Fusion Piano Transcription Model Based on the Attention Mechanism;IEEE/ACM Transactions on Audio, Speech, and Language Processing;2024