(1) Deep Learning for Machine Intelligence

                        Single Depth Image Super-Resolution Using Convolutional Neural Networks

                        A Fast Deconvolution-Based Approach for Single Image Super-resolution with GPU Acceleration

                        Deep Feature Embedding Learning for Person Re-Identification Using Lifted Structured Loss

                        Automatic Segmentation and Cardiopathy Classification in Cardiac MRI Images Based on Fully Convolutional Neural Networks

                        TV-SVM: Support Vector Machine with Total Variational Regularization

                        (2) Stereoscopic 3D Video Processing

                        Perceptual stereoscopic video coding using depth-of-focus blur effects

                        Example-based video stereolization (EBVS) for 2D-to-3D conversion

                        Joint geodesic depth propagation and depth up-sampling

                        Visual comfort assessment and enhancement based on saliency and DIBR

                        Reliability-based discontinuity-preserving stereo matching

                        (3) Multimedia Annotation and Retrieval

                        Semantic annotation based on semi-supervised learning and constraint propagation

                        Kernel sparse representation-based classification using multi-objective optimization

                        Content-based summarization and retrieval for news and sports videos

                        Interactive image retrieval by active learning from relevance feedback

                        Videotext detection, segmentation, and recognition

                        (4) Image Super-resolution

                        Novel Bayesian deringing method using spatial-gradient-local-inhomogeniety prior

                        Face super-resolution based on convex optimization (l1-norm)

                        Parallelization of super-resolution reconstruction on GPU and multi-core platforms

                        Curvature-preserving super-resolution with gradient-consistency-anisotropic-regularization prior

                        Dictionary-based super-resolution with nonlocal total variation regularization

                        (5) Computational Photography

                        High dynamic range imaging by tone mapping and multi-exposure fusion

                        Specularity removal in color images

                        Interactive image segmentation by user interactions such as makers and touch

                        Power-constrained contrast enhancement for low power LCD displays

                        (6) Perceptual Video Coding and H.265

                        Perceptual image/video coding using human color perception

                        Perceptual rate distortion optimization using free energy principles and structural similarity

                        Blocking artifact reduction using sparse representation

                        Perceptual block merging for quad-tree based partitioning in H.265

                        Motion compensated prediction and interpolation in H.265

                        Projects

                        Xidian Media Lab has been supported by:

                        (1) Organization Department of the CPC Central Committee
                        (2) National Natural Science Foundation of China
                        (3) Ministry of Science and Technology
                        (4) China Postdoctoral Science Foundation
                        (5) Novatek Electronics
                        (6) Samsung SDS
                        (7) Huawei Technologies
                        (8) ZTE Corporation
                        (9) Institute of Information and Communication Technology Promotion (IITP)

                        We would like to acknowledge their financial support for our research.


                        ?2015 Xidian Media Lab. All rights reserved.
                        Email: jushutaoxidian@163.com

                              
                              

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