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Yi Liu
Researcher at Xidian University
Publications - 8
Citations - 421
Yi Liu is an academic researcher from Xidian University. The author has contributed to research in topics: Computer science & Sparse approximation. The author has an hindex of 4, co-authored 4 publications receiving 255 citations.
Papers
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Journal ArticleDOI
Sparse representation based multi-sensor image fusion for multi-focus and multi-modality images: A review
TL;DR: A systematic review of the SR-based multi-sensor image fusion literature, highlighting the pros and cons of each category of approaches and evaluating the impact of these three algorithmic components on the fusion performance when dealing with different applications.
Proceedings ArticleDOI
Employing Deep Part-Object Relationships for Salient Object Detection
TL;DR: Experimental results demonstrate the superiority of the proposed salient object detection network over the state-of-the-art methods.
Journal ArticleDOI
Salient object detection based on super-pixel clustering and unified low-rank representation
TL;DR: This paper presents a novel salient object detection method, efficiently combining Laplacian sparse subspace clustering (LSSC) and unified low-rank representation (ULRR), which succeeds in extracting large-size salient objects from cluttered backgrounds, against the detection of small-size relevant objects from simple backgrounds obtained by most existing work.
Journal ArticleDOI
Bi-Directional Progressive Guidance Network for RGB-D Salient Object Detection
TL;DR: A Bi-directional Progressive Guidance Network (BPGNet) for RGB-D salient object detection, where the qualities of both RGB and depth images are involved, and experimental results demonstrate that the proposed model is comparable to those of state-of-the-artRGB-D SOD models.
Posted Content
Sparse Representation based Multi-sensor Image Fusion: A Review
TL;DR: A systematic review of the SR-based multi-sensor image fusion literature, highlighting the pros and cons of each category of approaches and evaluating the impact of these three algorithmic components on the fusion performance when dealing with different applications.