activity
20182022
most citedDense Attention Fluid Network for Salient Object Detection in Optical Remote Sensing Images

348 citations · 610 across the 30 of their papers we have counts for

collaborators

39 papers

cs.CV20215 cited

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…

cs.CV20214 cited

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…

cs.CV2021

Contrastive Semantic Similarity Learning for Image Captioning Evaluation with Intrinsic Auto-encoder

Chao Zeng, Tiesong Zhao, Sam Kwong

Automatically evaluating the quality of image captions can be very challenging since human language is quite flexible that there can be various expressions for the same meaning. Mo…

cs.LG20212 cited

Self-supervised Symmetric Nonnegative Matrix Factorization

Yuheng Jia, Hui Liu, Junhui Hou +2

Symmetric nonnegative matrix factorization (SNMF) has demonstrated to be a powerful method for data clustering. However, SNMF is mathematically formulated as a non-convex optimizat…

cs.AI2021

On the Philosophical, Cognitive and Mathematical Foundations of Symbiotic Autonomous Systems (SAS)

Yingxu Wang, Fakhri Karray, Sam Kwong +12

Symbiotic Autonomous Systems (SAS) are advanced intelligent and cognitive systems exhibiting autonomous collective intelligence enabled by coherent symbiosis of human-machine inter…

cs.CV2021

Camera Invariant Feature Learning for Generalized Face Anti-spoofing

Baoliang Chen, Wenhan Yang, Haoliang Li +2

There has been an increasing consensus in learning based face anti-spoofing that the divergence in terms of camera models is causing a large domain gap in real application scenario…