1 code implementation • 20 May 2022 • Jing Lin, Xiaowan Hu, Yuanhao Cai, Haoqian Wang, Youliang Yan, Xueyi Zou, Yulun Zhang, Luc van Gool
On the other hand, we equip the sequence-to-sequence model with an unsupervised optical flow estimator to maximize its potential.
Ranked #2 on Video Enhancement on MFQE v2
2 code implementations • NeurIPS 2021 • Yuanhao Cai, Xiaowan Hu, Haoqian Wang, Yulun Zhang, Hanspeter Pfister, Donglai Wei
Additionally, for better noise fitting, we present an efficient architecture Simple Multi-scale Network (SMNet) as the generator.
Ranked #1 on Noise Estimation on SIDD
1 code implementation • 9 Mar 2022 • Yuanhao Cai, Jing Lin, Xiaowan Hu, Haoqian Wang, Xin Yuan, Yulun Zhang, Radu Timofte, Luc van Gool
Many algorithms have been developed to solve the inverse problem of coded aperture snapshot spectral imaging (CASSI), i. e., recovering the 3D hyperspectral images (HSIs) from a 2D compressive measurement.
Ranked #2 on Spectral Reconstruction on Real HSI
2 code implementations • CVPR 2022 • Xiaowan Hu, Yuanhao Cai, Jing Lin, Haoqian Wang, Xin Yuan, Yulun Zhang, Radu Timofte, Luc van Gool
On the one hand, the proposed HR spatial-spectral attention module with its efficient feature fusion provides continuous and fine pixel-level features.
Ranked #5 on Spectral Reconstruction on Real HSI
1 code implementation • 6 Jan 2022 • Jing Lin, Yuanhao Cai, Xiaowan Hu, Haoqian Wang, Youliang Yan, Xueyi Zou, Henghui Ding, Yulun Zhang, Radu Timofte, Luc van Gool
Exploiting similar and sharper scene patches in spatio-temporal neighborhoods is critical for video deblurring.
Ranked #1 on Deblurring on DVD
3 code implementations • CVPR 2022 • Yuanhao Cai, Jing Lin, Xiaowan Hu, Haoqian Wang, Xin Yuan, Yulun Zhang, Radu Timofte, Luc van Gool
The HSI representations are highly similar and correlated across the spectral dimension.
Ranked #2 on Spectral Reconstruction on ARAD-1K
no code implementations • CVPR 2021 • Xiaowan Hu, Ruijun Ma, Zhihong Liu, Yuanhao Cai, Xiaole Zhao, Yulun Zhang, Haoqian Wang
The extraction of auto-correlation in images has shown great potential in deep learning networks, such as the self-attention mechanism in the channel domain and the self-similarity mechanism in the spatial domain.