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Multi-Projection Fusion and Refinement Network for Salient Object Detection in 360° Omnidirectional Image
Runmin Cong, Ke Huang, Jianjun Lei +3
Salient object detection (SOD) aims to determine the most visually attractive objects in an image. With the development of virtual reality technology, 360° omnidirectional image ha…
Bridging Component Learning with Degradation Modelling for Blind Image Super-Resolution
Yixuan Wu, Feng Li, Huihui Bai +3
Convolutional Neural Network (CNN)-based image super-resolution (SR) has exhibited impressive success on known degraded low-resolution (LR) images. However, this type of approach i…
Learning Detail-Structure Alternative Optimization for Blind Super-Resolution
Feng Li, Yixuan Wu, Huihui Bai +3
Existing convolutional neural networks (CNN) based image super-resolution (SR) methods have achieved impressive performance on bicubic kernel, which is not valid to handle unknown…
Feedback Chain Network For Hippocampus Segmentation
Heyu Huang, Runmin Cong, Lianhe Yang +3
The hippocampus plays a vital role in the diagnosis and treatment of many neurological disorders. Recent years, deep learning technology has made great progress in the field of med…
PSNet: Parallel Symmetric Network for Video Salient Object Detection
Runmin Cong, Weiyu Song, Jianjun Lei +3
For the video salient object detection (VSOD) task, how to excavate the information from the appearance modality and the motion modality has always been a topic of great concern. T…
Does Thermal Really Always Matter for RGB-T Salient Object Detection?
Runmin Cong, Kepu Zhang, Chen Zhang +4
In recent years, RGB-T salient object detection (SOD) has attracted continuous attention, which makes it possible to identify salient objects in environments such as low light by i…