Despite being highly secure, vein recognition suffers from the high inter-class similarity and intra-class variation resulting from the uncontrolled image […]
Despite the great success achieved by convolutional neural networks (CNNs) in various image understanding tasks, it is still difficult for […]
The objective of our work is to reconstruct 3D object instances from a single RGB image of a cluttered scene. […]
In this paper, we propose a novel color-texture image segmentation method based on local histograms. Starting with clustering-based color quantization, […]
In this paper, we propose the first framework (UCNet) to employ uncertainty for RGB-D saliency detection by learning from the […]
Osteoporosis makes bones weak and brittle, increasing the risk of fracture. In this paper, we designed a hybrid model to […]
Image corners have been widely used in various computer vision tasks. Current multi-scale analysis based corner detectors do not make […]
In underwater scenes, wavelength-dependent light absorption and scattering degrade the visibility of images and videos. The degraded underwater images and […]
Deep convolutional networks based super-resolution is a fast-growing field with numerous practical applications. In this exposition, we extensively compare 30+ […]
Corners are important features for image analysis and computer vision tasks. Local structure tensors with multiple scales are widely used […]
