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Yunjin Chen
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2020 – today
- 2024
- [j19]Minglang Qiao
, Mai Xu
HyperSOR: Context-Aware Graph Hypernetwork for Salient Object Ranking. IEEE Trans. Pattern Anal. Mach. Intell. 46(9): 5873-5889 (2024) - [c15]Minglang Qiao, Mai Xu, Shijie Wen, Lai Jiang, Shengxi Li, Tao Xu, Yunjin Chen, Leonid Sigal:
Saliency Prediction of Sports Videos: A Large-Scale Database and a Self-Adaptive Approach. ICASSP 2024: 6615-6619 - 2023
- [c14]Mingdeng Cao, Chong Mou, Fanghua Yu, Xintao Wang, Yinqiang Zheng, Jian Zhang, Chao Dong, Gen Li, Ying Shan, Radu Timofte
NTIRE 2023 Challenge on 360° Omnidirectional Image and Video Super-Resolution: Datasets, Methods and Results. CVPR Workshops 2023: 1731-1745 - [c13]Yawei Li
NTIRE 2023 Challenge on Image Denoising: Methods and Results. CVPR Workshops 2023: 1905-1921 - [c12]Yichen Guo, Mai Xu, Lai Jiang, Leonid Sigal, Yunjin Chen:
DINN360: Deformable Invertible Neural Network for Latitude-aware 360° Image Rescaling. CVPR 2023: 21519-21528 - [c11]Qiuyue Fang, Tao Xu, Lai Jiang, Shengxi Li, Mai Xu, Yunjin Chen, Leonid Sigal:
Optimizing DNN based quality assessment metric for image compression: A novel rate control method. ICME 2023: 714-719 - 2022
- [j18]Xin Cui
Semi-Supervised Image Deraining Using Knowledge Distillation. IEEE Trans. Circuits Syst. Video Technol. 32(12): 8327-8341 (2022) - [c10]Ren Yang
NTIRE 2022 Challenge on Super-Resolution and Quality Enhancement of Compressed Video: Dataset, Methods and Results. CVPR Workshops 2022: 1220-1237 - [c9]Zhilu Zhang, Ruohao Wang, Hongzhi Zhang, Yunjin Chen, Wangmeng Zuo:
Self-supervised Learning for Real-World Super-Resolution from Dual Zoomed Observations. ECCV (18) 2022: 610-627 - [i18]Zhilu Zhang, Ruohao Wang, Hongzhi Zhang, Yunjin Chen, Wangmeng Zuo:
Self-Supervised Learning for Real-World Super-Resolution from Dual Zoomed Observations. CoRR abs/2203.01325 (2022) - [i17]Ren Yang, Radu Timofte, Meisong Zheng, Qunliang Xing, Minglang Qiao, Mai Xu, Lai Jiang, Huaida Liu, Ying Chen, Youcheng Ben, Xiao Zhou, Chen Fu, Pei Cheng, Gang Yu
NTIRE 2022 Challenge on Super-Resolution and Quality Enhancement of Compressed Video: Dataset, Methods and Results. CoRR abs/2204.09314 (2022) - 2020
- [j17]Shuhang Gu
Learned Dynamic Guidance for Depth Image Reconstruction. IEEE Trans. Pattern Anal. Mach. Intell. 42(10): 2437-2452 (2020)
2010 – 2019
- 2019
- [c8]Bingshan Hu, Yunjin Chen, Zhiming Huang
Intelligent Caching Algorithms in Heterogeneous Wireless Networks with Uncertainty. ICDCS 2019: 1549-1558 - 2018
- [j16]Zhihuo Xu
Non-stationary speckle reduction in high resolution SAR images. Digit. Signal Process. 73: 72-82 (2018) - [j15]WenSen Feng, Peng Qiao, Yunjin Chen
Fast and Accurate Poisson Denoising With Trainable Nonlinear Diffusion. IEEE Trans. Cybern. 48(6): 1708-1719 (2018) - [j14]Hu Chen
LEARN: Learned Experts' Assessment-Based Reconstruction Network for Sparse-Data CT. IEEE Trans. Medical Imaging 37(6): 1333-1347 (2018) - [c7]Peng Qiao, Yong Dou, Yunjin Chen, WenSen Feng:
Learning Generic Diffusion Processes for Image Restoration. BMVC 2018: 292 - [i16]Peng Qiao, Yong Dou, Yunjin Chen, WenSen Feng:
Learning Generic Diffusion Processes for Image Restoration. CoRR abs/1807.06216 (2018) - 2017
- [j13]WenSen Feng, Yunjin Chen:
Speckle Reduction with Trained Nonlinear Diffusion Filtering. J. Math. Imaging Vis. 58(1): 162-178 (2017) - [j12]Yunjin Chen, Thomas Pock:
Trainable Nonlinear Reaction Diffusion: A Flexible Framework for Fast and Effective Image Restoration. IEEE Trans. Pattern Anal. Mach. Intell. 39(6): 1256-1272 (2017) - [j11]WenSen Feng, Peng Qiao, Xuanyang Xi, Yunjin Chen:
Image Denoising via Multiscale Nonlinear Diffusion Models. SIAM J. Imaging Sci. 10(3): 1234-1257 (2017) - [j10]Yunjin Chen:
Variational JPEG artifacts suppression based on high-order MRFs. Signal Process. Image Commun. 52: 33-40 (2017) - [j9]Peng Qiao, Yunjin Chen, Yong Dou:
Variational single image interpolation with time-varying regularization. Signal Process. Image Commun. 58: 258-269 (2017) - [j8]Haiyan Fan
Hyperspectral Image Restoration Using Low-Rank Tensor Recovery. IEEE J. Sel. Top. Appl. Earth Obs. Remote. Sens. 10(10): 4589-4604 (2017) - [j7]Kai Zhang
Beyond a Gaussian Denoiser: Residual Learning of Deep CNN for Image Denoising. IEEE Trans. Image Process. 26(7): 3142-3155 (2017) - [c6]Qingyong Hu, Yulan Guo, Yunjin Chen, Jingjing Xiao, Wei An:
Correlation Filter Tracking: Beyond an Open-loop System. BMVC 2017 - [c5]Shuhang Gu, Wangmeng Zuo, Shi Guo, Yunjin Chen, Chongyu Chen, Lei Zhang:
Learning Dynamic Guidance for Depth Image Enhancement. CVPR 2017: 712-721 - [c4]Radu Timofte
NTIRE 2017 Challenge on Single Image Super-Resolution: Methods and Results. CVPR Workshops 2017: 1110-1121 - [c3]Peng Qiao, Yong Dou, WenSen Feng, Rongchun Li, Yunjin Chen:
Learning Non-local Image Diffusion for Image Denoising. ACM Multimedia 2017: 1847-1855 - [i15]Peng Qiao, Yong Dou, WenSen Feng, Yunjin Chen:
Learning Non-local Image Diffusion for Image Denoising. CoRR abs/1702.07472 (2017) - [i14]WenSen Feng, Yunjin Chen:
Speckle Reduction with Trained Nonlinear Diffusion Filtering. CoRR abs/1702.07482 (2017) - 2016
- [j6]Yunjin Chen:
Higher-order MRFs based image super resolution: why not MAP? IET Image Process. 10(4): 297-303 (2016) - [j5]WenSen Feng, Hong Qiao, Yunjin Chen:
Poisson Noise Reduction with Higher-Order Natural Image Prior Model. SIAM J. Imaging Sci. 9(3): 1502-1524 (2016) - [j4]Xiangli Nie, Bo Zhang
A New Algorithm for Optimizing TV-Based PolSAR Despeckling Model. IEEE Signal Process. Lett. 23(10): 1409-1413 (2016) - [i13]Kai Zhang
Beyond a Gaussian Denoiser: Residual Learning of Deep CNN for Image Denoising. CoRR abs/1608.03981 (2016) - [i12]WenSen Feng, Hong Qiao, Yunjin Chen:
Poisson Noise Reduction with Higher-order Natural Image Prior Model. CoRR abs/1609.05722 (2016) - [i11]WenSen Feng, Peng Qiao, Xuanyang Xi, Yunjin Chen:
Image Denoising via Multi-scale Nonlinear Diffusion Models. CoRR abs/1609.06585 (2016) - 2015
- [c2]Yunjin Chen, Wei Yu, Thomas Pock:
On learning optimized reaction diffusion processes for effective image restoration. CVPR 2015: 5261-5269 - [i10]Yunjin Chen, Wei Yu, Thomas Pock:
On learning optimized reaction diffusion processes for effective image restoration. CoRR abs/1503.05768 (2015) - [i9]Yunjin Chen, Thomas Pock:
Trainable Nonlinear Reaction Diffusion: A Flexible Framework for Fast and Effective Image Restoration. CoRR abs/1508.02848 (2015) - [i8]WenSen Feng, Yunjin Chen:
Fast and Accurate Poisson Denoising with Optimized Nonlinear Diffusion. CoRR abs/1510.02930 (2015) - 2014
- [j3]Peter Ochs, Yunjin Chen, Thomas Brox, Thomas Pock:
iPiano: Inertial Proximal Algorithm for Nonconvex Optimization. SIAM J. Imaging Sci. 7(2): 1388-1419 (2014) - [j2]Yunjin Chen, WenSen Feng, René Ranftl, Hong Qiao, Thomas Pock:
A Higher-Order MRF Based Variational Model for Multiplicative Noise Reduction. IEEE Signal Process. Lett. 21(11): 1370-1374 (2014) - [j1]Yunjin Chen, René Ranftl, Thomas Pock:
Insights Into Analysis Operator Learning: From Patch-Based Sparse Models to Higher Order MRFs. IEEE Trans. Image Process. 23(3): 1060-1072 (2014) - [i7]Yunjin Chen, René Ranftl, Thomas Pock:
Insights into analysis operator learning: From patch-based sparse models to higher-order MRFs. CoRR abs/1401.2804 (2014) - [i6]Yunjin Chen, Thomas Pock, Horst Bischof:
Learning ℓ1-based analysis and synthesis sparsity priors using bi-level optimization. CoRR abs/1401.4105 (2014) - [i5]Yunjin Chen, Thomas Pock, René Ranftl, Horst Bischof:
Revisiting loss-specific training of filter-based MRFs for image restoration. CoRR abs/1401.4107 (2014) - [i4]Yunjin Chen, René Ranftl, Thomas Pock:
A bi-level view of inpainting - based image compression. CoRR abs/1401.4112 (2014) - [i3]Peter Ochs, Yunjin Chen, Thomas Brox, Thomas Pock:
iPiano: Inertial Proximal Algorithm for Non-Convex Optimization. CoRR abs/1404.4805 (2014) - [i2]Yunjin Chen, WenSen Feng, René Ranftl, Hong Qiao, Thomas Pock:
A higher-order MRF based variational model for multiplicative noise reduction. CoRR abs/1404.5344 (2014) - [i1]Yunjin Chen:
Higher-order MRFs based image super resolution: MMSE or MAP? CoRR abs/1410.7429 (2014) - 2013
- [c1]Yunjin Chen, Thomas Pock, René Ranftl, Horst Bischof
Revisiting Loss-Specific Training of Filter-Based MRFs for Image Restoration. GCPR 2013: 271-281
Coauthor Index
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