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RRNet: Relational Reasoning Network with Parallel Multi-scale Attention for Salient Object Detection in Optical Remote Sensing Images
Runmin Cong, Yumo Zhang, Leyuan Fang +3
Salient object detection (SOD) for optical remote sensing images (RSIs) aims at locating and extracting visually distinctive objects/regions from the optical RSIs. Despite some sal…
Cross-modality Discrepant Interaction Network for RGB-D Salient Object Detection
Chen Zhang, Runmin Cong, Qinwei Lin +4
The popularity and promotion of depth maps have brought new vigor and vitality into salient object detection (SOD), and a mass of RGB-D SOD algorithms have been proposed, mainly co…
BridgeNet: A Joint Learning Network of Depth Map Super-Resolution and Monocular Depth Estimation
Qi Tang, Runmin Cong, Ronghui Sheng +4
Depth map super-resolution is a task with high practical application requirements in the industry. Existing color-guided depth map super-resolution methods usually necessitate an e…
Underwater Image Enhancement via Medium Transmission-Guided Multi-Color Space Embedding
Chongyi Li, Saeed Anwar, Junhui Hou +3
Underwater images suffer from color casts and low contrast due to wavelength- and distance-dependent attenuation and scattering. To solve these two degradation issues, we present a…
Towards Fast and Accurate Real-World Depth Super-Resolution: Benchmark Dataset and Baseline
Lingzhi He, Hongguang Zhu, Feng Li +6
Depth maps obtained by commercial depth sensors are always in low-resolution, making it difficult to be used in various computer vision tasks. Thus, depth map super-resolution (SR)…