Faster nonconvex low-rank matrix learning for image low-level and high-level vision: A unified framework

Hengmin Zhang, Jian Yang, Jianjun Qian, Chen Gong, Xin Ning, Zhiyuan Zha, Bihan Wen

Abstract: Highlights•Integrating nonconvex estimators serves to enhance learning capabilities;•Introducing a unified framework generalizes multiple rank-relaxed problems;•The combination of RSVD and continuity techniques yields an efficient solver;•The superiority is established and reinforced through experimental validations.