Projects

Visual Information Science, Technology and Application Laboratory

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Defogging Quality Assessment using FRFSIM: Results and Comparisons
Direct Application of Convolutional Neural Network Features to Image Quality Assessment
Dual Adaptive Pyramid Network for Cross-Stain Histopathology Image Segmentation
Improving Variational Autoencoder with Deep Feature Consistent and Generative Adversarial Training
Indoor Topological Localization Using a Visual Landmark Sequence
Learning Deep Image Priors for Blind Image Denoising
Quality assessment database for super-resolved images: QADS
Relative Geometry-Aware Siamese Neural Network for 6DOF Camera Relocalization 
Side Window Filtering
- Results of Subwindows filter
Structure and Texture-Aware Image Decomposition via Training a Neural Network
- Result Of STD
test
projects

Click here to Quality assessment database for super-resolved images: QADS.