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SDDNet: Style-guided Dual-layer Disentanglement Network for Shadow Detection
Runmin Cong, Yuchen Guan, Jinpeng Chen +3
Despite significant progress in shadow detection, current methods still struggle with the adverse impact of background color, which may lead to errors when shadows are present on c…
Point-aware Interaction and CNN-induced Refinement Network for RGB-D Salient Object Detection
Runmin Cong, Hongyu Liu, Chen Zhang +4
By integrating complementary information from RGB image and depth map, the ability of salient object detection (SOD) for complex and challenging scenes can be improved. In recent y…
Frequency Perception Network for Camouflaged Object Detection
Runmin Cong, Mengyao Sun, Sanyi Zhang +3
Camouflaged object detection (COD) aims to accurately detect objects hidden in the surrounding environment. However, the existing COD methods mainly locate camouflaged objects in t…
You Can Mask More For Extremely Low-Bitrate Image Compression
Anqi Li, Feng Li, Jiaxin Han +6
Learned image compression (LIC) methods have experienced significant progress during recent years. However, these methods are primarily dedicated to optimizing the rate-distortion…
Exploring Resolution Fields for Scalable Image Compression with Uncertainty Guidance
Dongyi Zhang, Feng Li, Man Liu +4
Recently, there are significant advancements in learning-based image compression methods surpassing traditional coding standards. Most of them prioritize achieving the best rate-di…
PUGAN: Physical Model-Guided Underwater Image Enhancement Using GAN with Dual-Discriminators
Runmin Cong, Wenyu Yang, Wei Zhang +4
Due to the light absorption and scattering induced by the water medium, underwater images usually suffer from some degradation problems, such as low contrast, color distortion, and…