34 citations · 62 across the 6 of their papers we have counts for
7 papers
Arbitrary Virtual Try-On Network: Characteristics Preservation and Trade-off between Body and Clothing
Yu Liu, Mingbo Zhao, Zhao Zhang +2
Deep learning based virtual try-on system has achieved some encouraging progress recently, but there still remain several big challenges that need to be solved, such as trying on a…
MFAGAN: A Compression Framework for Memory-Efficient On-Device Super-Resolution GAN
Wenlong Cheng, Mingbo Zhao, Zhiling Ye +1
Generative adversarial networks (GANs) have promoted remarkable advances in single-image super-resolution (SR) by recovering photo-realistic images. However, high memory consumptio…
A Simple Approach to Automated Spectral Clustering
Jicong Fan, Yiheng Tu, Zhao Zhang +2
The performance of spectral clustering heavily relies on the quality of affinity matrix. A variety of affinity-matrix-construction (AMC) methods have been proposed but they have hy…
Deep Self-representative Concept Factorization Network for Representation Learning
Yan Zhang, Zhao Zhang, Zheng Zhang +4
In this paper, we investigate the unsupervised deep representation learning issue and technically propose a novel framework called Deep Self-representative Concept Factorization Ne…
Robust Triple-Matrix-Recovery-Based Auto-Weighted Label Propagation for Classification
Huan Zhang, Zhao Zhang, Mingbo Zhao +3
The graph-based semi-supervised label propagation algorithm has delivered impressive classification results. However, the estimated soft labels typically contain mixed signs and no…
Kernel-Induced Label Propagation by Mapping for Semi-Supervised Classification
Zhao Zhang, Lei Jia, Mingbo Zhao +3
Kernel methods have been successfully applied to the areas of pattern recognition and data mining. In this paper, we mainly discuss the issue of propagating labels in kernel space.…
NDDR-CNN: Layerwise Feature Fusing in Multi-Task CNNs by Neural Discriminative Dimensionality Reduction
Yuan Gao, Jiayi Ma, Mingbo Zhao +2
In this paper, we propose a novel Convolutional Neural Network (CNN) structure for general-purpose multi-task learning (MTL), which enables automatic feature fusing at every layer…