Wanjun Chen
MediaTech Institute
6 Papers
11 Citations
Wanjun Chen is an academic researcher from MediaTech Institute. The author has contributed to research in topics: Computer science & Depth map. The author has an hindex of 4, co-authored 5 publications.
Chat about Author
Papers
Deep neural network for halftone image classification based on sparse auto-encoder
Yan Zhang,Erhu Zhang,Wanjun Chen +2 more
TL;DR: Compared with state-of-the-art LMS-Bayes and M 10 - ML methods, the proposed SAE-MV method can distinguish the most categories of halftone images and achieve competitive ACCR, meanwhile, demonstrate better generalization performance.
115
Sparsity-based inverse halftoning via semi-coupled multi-dictionary learning and structural clustering
TL;DR: The experimental results demonstrate that the proposed inverse halftoning method can restore higher quality continuous-tone images than that produced by the state-of-the-art methods, which not only reduce the screen noise in smooth regions, but also provide well fine details and clear edges.
27
A Laplacian structured representation model in subspace clustering for enhanced motion segmentation
TL;DR: A Laplacian structured representation model is proposed to enhance the representation-based clustering methods by importing local feature similarity prior information to guide the encoding process, and an efficient Alternating Direction Method of Multipliers (ADMM) algorithm for optimization is developed.
12
Weather Radar Echo Extrapolation Method Based on Deep Learning
Fugui Zhang,Can Lai,Wanjun Chen +2 more
TL;DR: The results demonstrate that the radar echo extrapolation method based on deep learning is obviously more accurate and stable than traditional radar echo interpolation methods in near weather forecasting.
Integrating Complementary Appearance, Posture and Motion Cues for RGB-D Action Recognition
Wanjun Chen,Erhu Zhang,Yan Zhang +2 more
TL;DR: This work presents a novel approach to multimodal human action recognition by jointly using visual RGB and depth data captured from depth camera, which outperforms or is comparable to the state-of-the-art methods.
3