124 citations · 463 across the 16 of their papers we have counts for
10 papers · 1 filter
Rethinking of the Image Salient Object Detection: Object-level Semantic Saliency Re-ranking First, Pixel-wise Saliency Refinement Latter
Zhenyu Wu, Shuai Li, Chenglizhao Chen +2
The real human attention is an interactive activity between our visual system and our brain, using both low-level visual stimulus and high-level semantic information. Previous imag…
Data-Level Recombination and Lightweight Fusion Scheme for RGB-D Salient Object Detection
Xuehao Wang, Shuai Li, Chenglizhao Chen +3
Existing RGB-D salient object detection methods treat depth information as an independent component to complement its RGB part, and widely follow the bi-stream parallel network arc…
Full Reference Screen Content Image Quality Assessment by Fusing Multi-level Structure Similarity
Chenglizhao Chen, Hongmeng Zhao, Huan Yang +2
The screen content images (SCIs) usually comprise various content types with sharp edges, in which the artifacts or distortions can be well sensed by the vanilla structure similari…
Depth Quality Aware Salient Object Detection
Chenglizhao Chen, Jipeng Wei, Chong Peng +1
The existing fusion based RGB-D salient object detection methods usually adopt the bi-stream structure to strike the fusion trade-off between RGB and depth (D). The D quality usual…
Recursive Multi-model Complementary Deep Fusion forRobust Salient Object Detection via Parallel Sub Networks
Zhenyu Wu, Shuai Li, Chenglizhao Chen +2
Fully convolutional networks have shown outstanding performance in the salient object detection (SOD) field. The state-of-the-art (SOTA) methods have a tendency to become deeper an…
Knowing Depth Quality In Advance: A Depth Quality Assessment Method For RGB-D Salient Object Detection
Xuehao Wang, Shuai Li, Chenglizhao Chen +2
Previous RGB-D salient object detection (SOD) methods have widely adopted deep learning tools to automatically strike a trade-off between RGB and D (depth), whose key rationale is…
Exploring Rich and Efficient Spatial Temporal Interactions for Real Time Video Salient Object Detection
Chenglizhao Chen, Guotao Wang, Chong Peng +3
The current main stream methods formulate their video saliency mainly from two independent venues, i.e., the spatial and temporal branches. As a complementary component, the main t…
A Deeper Look at Salient Object Detection: Bi-stream Network with a Small Training Dataset
Zhenyu Wu, Shuai Li, Chenglizhao Chen +2
Compared with the conventional hand-crafted approaches, the deep learning based methods have achieved tremendous performance improvements by training exquisitely crafted fancy netw…
A Plug-and-play Scheme to Adapt Image Saliency Deep Model for Video Data
Yunxiao Li, Shuai Li, Chenglizhao Chen +2
With the rapid development of deep learning techniques, image saliency deep models trained solely by spatial information have occasionally achieved detection performance for video…
Deep Patch-based Human Segmentation
Dongbo Zhang, Zheng Fang, Xuequan Lu +4
3D human segmentation has seen noticeable progress in re-cent years. It, however, still remains a challenge to date. In this paper, weintroduce a deep patch-based method for 3D hum…