no code implementations • 9 Jun 2023 • Junyu Wang
We present an efficient speech separation neural network, ARFDCN, which combines dilated convolutions, multi-scale fusion (MSF), and channel attention to overcome the limited receptive field of convolution-based networks and the high computational cost of transformer-based networks.
no code implementations • 9 Jun 2023 • Junyu Wang
Current speech enhancement (SE) research has largely neglected channel attention and spatial attention, and encoder-decoder architecture-based networks have not adequately considered how to provide efficient inputs to the intermediate enhancement layer.
1 code implementation • 16 May 2023 • Junyu Wang, Shijie Wang, Ruijie Zhang, Zengqiang Zheng, Wenyu Liu, Xinggang Wang
We present RND-SCI, a novel framework for compressive hyperspectral image (HSI) reconstruction.
1 code implementation • 24 Jan 2023 • Junyu Wang, Shijie Wang, Wenyu Liu, Zengqiang Zheng, Xinggang Wang
We present a simple, efficient, and scalable unfolding network, SAUNet, to simplify the network design with an adaptive alternate optimization framework for hyperspectral image (HSI) reconstruction.