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- University of Science and Technology of ChinaCN178 papers
- Chinese Academy of SciencesCN47 papers
- Anhui UniversityCN46 papers
- National University of SingaporeSG36 papers
- Hefei National Center for Physical Sciences at NanoscaleCN29 papers
- Tsinghua UniversityCN24 papers
- Peking UniversityCN20 papers
- Zhejiang UniversityCN17 papers
- Eindhoven University of TechnologyNL16 papers
- Harbin Institute of TechnologyCN14 papers
- Soochow UniversityCN14 papers
- University of Chinese Academy of SciencesCN12 papers
17 papers · 2 filters
DerainCycleGAN: Rain Attentive CycleGAN for Single Image Deraining and Rainmaking
Yanyan Wei, Zhao Zhang, Yang Wang +4
Single image deraining (SID) is an important and challenging topic in emerging vision applications, and most of emerged deraining methods are supervised relying on the ground truth…
Discriminative Local Sparse Representation by Robust Adaptive Dictionary Pair Learning
Yulin Sun, Zhao Zhang, Weiming Jiang +4
In this paper, we propose a structured Robust Adaptive Dic-tionary Pair Learning (RA-DPL) framework for the discrim-inative sparse representation learning. To achieve powerful repr…
Flexible Auto-weighted Local-coordinate Concept Factorization: A Robust Framework for Unsupervised Clustering
Zhao Zhang, Yan Zhang, Sheng Li +4
Concept Factorization (CF) and its variants may produce inaccurate representation and clustering results due to the sensitivity to noise, hard constraint on the reconstruction erro…
Adaptive Structure-constrained Robust Latent Low-Rank Coding for Image Recovery
Zhao Zhang, Lei Wang, Sheng Li +4
In this paper, we propose a robust representation learning model called Adaptive Structure-constrained Low-Rank Coding (AS-LRC) for the latent representation of data. To recover th…
Learning Structured Twin-Incoherent Twin-Projective Latent Dictionary Pairs for Classification
Zhao Zhang, Yulin Sun, Zheng Zhang +3
In this paper, we extend the popular dictionary pair learning (DPL) into the scenario of twin-projective latent flexible DPL under a structured twin-incoherence. Technically, a nov…
Robust Subspace Discovery by Block-diagonal Adaptive Locality-constrained Representation
Zhao Zhang, Jiahuan Ren, Sheng Li +3
We propose a novel and unsupervised representation learning model, i.e., Robust Block-Diagonal Adaptive Locality-constrained Latent Representation (rBDLR). rBDLR is able to recover…