Research

Deep Learning for Image Denoising

Recorrupted-to-Recorrupted: Unsupervised deep learning for image denoising
Image denoising using complex-valued deep CNN
Self2Self with dropout: Learning self-supervised denoising from single image
Image denoising via sequential ensemble learning

Unsupervised Deep Learning for Computational Photography and Imaging

Self2Self: Self-Supervised Image Denoising

Self2Self with dropout: Learning self-supervised denoising from single image, CVPR, 2020. Self-supervised Bayesian deep learning for image recovery with applications to compressed sensing, ECCV, 2020.

Supervised Learning for Image Recovery

Image Denoising via Sequential Ensemble Learning

Image denoising via sequential ensemble learning, TIP, 2020.

Non-Blind Image Deblurring via Variational-EM-Based Deep Learning

Variational-EM-based deep learning for noise-blind image deblurring, CVPR, 2020.

Super-Resolving Blurry Text Images via Collaborative Deep Learning

Collaborative deep learning for super-resolving blurry text images, TCI, 2020.

Image Raindrop Removal via Shape Attention

Deep learning for seeing through window with raindrops, ICCV, 2019.

Intellectual Property Protection of Supervised Learning Systems in Image Recovery

Watermarking deep neural networks in image processing, TNNLS, 2020.

Exploiting Patch Recurrence for Image Processing

Data-Driven Multi-Scale Non-local Wavelet Frame Construction and Image Recovery

Data-driven multi-scale non-local wavelet frame construction and image recovery, JoSC, 2015.

Image Decomposition via Discriminative Patch Recurrence

Structure-texture image decomposition using discriminative patch recurrence, TIP, 2021. Cartoon-texture image decomposition using orientation characteristics in patch recurrence, SIIMS, 2020.

Removing Ghosting Reflections Using Discriminative Recurrence of Patterns

Removing reflection from a single image with ghosting effect, TCI, 2020.

Sparse Representation for Computer Vision and Image Processing

Sparse Coding for Classification: Improving Discrimination

Supervised sparse coding with decision forest, SPL, 2019. Supervised dictionary learning with multiple classifier integration, PR, 2016. Equiangular kernel dictionary learning with applications to dynamic texture analysis, CVPR, 2016. Sparse coding for classification via discrimination ensemble, CVPR, 2016 A convergent incoherent dictionary learning algorithm for sparse coding, ECCV, 2014.

Sparse Coding and Dictionary Learning on Tensors

Factorized tensor dictionary learning for visual tensor data completion, TMM, 2020. Exploiting global low-rank structure and local sparsity nature for tensor completion, TCYB, 2019. Dynamic texture recognition via orthogonal tensor dictionary learning, ICCV, 2015.

Sparse Coding for Texture Analysis

Weakly-supervised sparse coding with geometric prior for interactive texture segmentation, SPL, 2020. Equiangular kernel dictionary learning with applications to dynamic texture analysis, CVPR, 2016. Dynamic texture recognition via orthogonal tensor dictionary learning, ICCV, 2015.

Sparse Coding for Image Quality Assessment

Image quality assessment using kernel sparse coding, TMM, 2020. Full-reference image quality metric for blurry images and compressed images using hybrid dictionary learning, NCA, 2020.

Sparse Coding: Algorithms and Convergence Analysis

Dictionary learning for sparse coding：Algorithms and convergence analysis, TPAMI, 2016. L0 norm-based dictionary learning by proximal methods with global convergence, CVPR, 2014.

Visual Quality Assessment: Local Measurements and Global Statistics

Visual Quality Assessment: Sparse Coding Approaches

Full-reference image quality metric for blurry images and compressed images using hybrid dictionary learning, NCA, 2020. Image quality assessment using kernel sparse coding, TMM, 2020.

Measuring Local Image Distortions

Estimating defocus blur via rank of local patches, ICCV, 2017.

Spatial-Distribution-Aware Image Quality Assessment

Fractal analysis for reduced reference image quality assessment, TIP, 2015. Directional regularity for visual quality estimation, SP, 2015. Reduced reference image quality assessment using regularity of phase congruency, SPIC, 2014.

Invariant Features for Visual Recognition

Lacunarity/Fractal Statistics for Texture Recognition

Spatiotemporal lacunarity spectrum for dynamic texture classification, CVIU, 2017. Characterizing dynamic textures with space-time lacunarity analysis, ICME, 2015. Lacunarity analysis on image patterns for texture classification, CVPR, 2014. Classifying dynamic textures via spatiotemporal fractal analysis, PR, 2015. A distinct and compact texture descriptor, IVC, 2014. Dynamic texture classification using dynamic fractal analysis, ICCV, 2011.

Maximum-Torque Contour Descriptor

Contour-based recognition, CVPR, 2012.