1 code implementation • 15 May 2023 • Yuanzhi Zhu, Kai Zhang, Jingyun Liang, JieZhang Cao, Bihan Wen, Radu Timofte, Luc van Gool
Although diffusion models have shown impressive performance for high-quality image synthesis, their potential to serve as a generative denoiser prior to the plug-and-play IR methods remains to be further explored.
no code implementations • CVPR 2023 • Lei Sun, Christos Sakaridis, Jingyun Liang, Peng Sun, JieZhang Cao, Kai Zhang, Qi Jiang, Kaiwei Wang, Luc van Gool
The performance of video frame interpolation is inherently correlated with the ability to handle motion in the input scene.
no code implementations • 25 Aug 2022 • JieZhang Cao, Qin Wang, Jingyun Liang, Yulun Zhang, Kai Zhang, Radu Timofte, Luc van Gool
To this end, we propose a new multi-scale refined optical flow-guided video denoising method, which is more robust to different noise levels.
Ranked #1 on Video Denoising on VideoLQ
1 code implementation • 25 Jul 2022 • JieZhang Cao, Jingyun Liang, Kai Zhang, Yawei Li, Yulun Zhang, Wenguan Wang, Luc van Gool
Reference-based image super-resolution (RefSR) aims to exploit auxiliary reference (Ref) images to super-resolve low-resolution (LR) images.
1 code implementation • 21 Jul 2022 • JieZhang Cao, Jingyun Liang, Kai Zhang, Wenguan Wang, Qin Wang, Yulun Zhang, Hao Tang, Luc van Gool
These issues can be alleviated by a cascade of three separate sub-tasks, including video deblurring, frame interpolation, and super-resolution, which, however, would fail to capture the spatial and temporal correlations among video sequences.
1 code implementation • 5 Jun 2022 • Jingyun Liang, Yuchen Fan, Xiaoyu Xiang, Rakesh Ranjan, Eddy Ilg, Simon Green, JieZhang Cao, Kai Zhang, Radu Timofte, Luc van Gool
Specifically, RVRT divides the video into multiple clips and uses the previously inferred clip feature to estimate the subsequent clip feature.
1 code implementation • 24 Mar 2022 • Kai Zhang, Yawei Li, Jingyun Liang, JieZhang Cao, Yulun Zhang, Hao Tang, Radu Timofte, Luc van Gool
While recent years have witnessed a dramatic upsurge of exploiting deep neural networks toward solving image denoising, existing methods mostly rely on simple noise assumptions, such as additive white Gaussian noise (AWGN), JPEG compression noise and camera sensor noise, and a general-purpose blind denoising method for real images remains unsolved.
1 code implementation • 28 Jan 2022 • Jingyun Liang, JieZhang Cao, Yuchen Fan, Kai Zhang, Rakesh Ranjan, Yawei Li, Radu Timofte, Luc van Gool
Besides, parallel warping is used to further fuse information from neighboring frames by parallel feature warping.
Ranked #1 on Deblurring on BASED
1 code implementation • 30 Nov 2021 • Lei Sun, Christos Sakaridis, Jingyun Liang, Qi Jiang, Kailun Yang, Peng Sun, Yaozu Ye, Kaiwei Wang, Luc van Gool
Traditional frame-based cameras inevitably suffer from motion blur due to long exposure times.
Ranked #3 on Deblurring on GoPro (using extra training data)
9 code implementations • 23 Aug 2021 • Jingyun Liang, JieZhang Cao, Guolei Sun, Kai Zhang, Luc van Gool, Radu Timofte
In particular, the deep feature extraction module is composed of several residual Swin Transformer blocks (RSTB), each of which has several Swin Transformer layers together with a residual connection.
Ranked #2 on Color Image Denoising on urban100 sigma15
1 code implementation • ICCV 2021 • Jingyun Liang, Andreas Lugmayr, Kai Zhang, Martin Danelljan, Luc van Gool, Radu Timofte
More specifically, HCFlow learns a bijective mapping between HR and LR image pairs by modelling the distribution of the LR image and the rest high-frequency component simultaneously.
1 code implementation • ICCV 2021 • Jingyun Liang, Guolei Sun, Kai Zhang, Luc van Gool, Radu Timofte
Extensive experiments on synthetic and real images show that the proposed MANet not only performs favorably for both spatially variant and invariant kernel estimation, but also leads to state-of-the-art blind SR performance when combined with non-blind SR methods.
no code implementations • 4 Aug 2021 • Guolei Sun, Yun Liu, Jingyun Liang, Luc van Gool
Due to the fact that fully supervised semantic segmentation methods require sufficient fully-labeled data to work well and can not generalize to unseen classes, few-shot segmentation has attracted lots of research attention.
1 code implementation • 12 Jun 2021 • JieZhang Cao, Yawei Li, Kai Zhang, Jingyun Liang, Luc van Gool
Specifically, to tackle the first issue, we present a spatial-temporal convolutional self-attention layer with a theoretical understanding to exploit the locality information.
1 code implementation • CVPR 2021 • Jingyun Liang, Kai Zhang, Shuhang Gu, Luc van Gool, Radu Timofte
Kernel estimation is generally one of the key problems for blind image super-resolution (SR).
3 code implementations • ICCV 2021 • Kai Zhang, Jingyun Liang, Luc van Gool, Radu Timofte
It is widely acknowledged that single image super-resolution (SISR) methods would not perform well if the assumed degradation model deviates from those in real images.
no code implementations • 22 Jul 2019 • Chengyu Guo, Jingyun Liang, Geng Zhan, Zhong Liu, Matti Pietikäinen, Li Liu
It is computationally efficient and only marginally increases the cost of computing LBPTOP, yet is extremely effective for ME recognition.