In this paper, as an application of fuzzy matroids, the fuzzifying greedy algorithm is proposed and an achievableexample is given. Basis axioms and circuit axioms of fuzzifying matroids, which are the semantic extension for thebasis axioms and circuit axioms of crisp matroids respectively, are presented. It is proved that a fuzzifying matroidis equivalent to a mapping which satisfies the basis ...

In traditional illustration the choice of appropriate styles and rendering techniques is guided by the intention of the artist. For illustrative volume visualizations it is difficult to specify the mapping between the 3D data and the visual representation that preserves the intention of the user. The semantic layers concept establishes this mapping with a linguistic formulation of rules that di...

Domain adaptive semantic segmentation attempts to make satisfactory dense predictions on an unlabeled target domain by utilizing the supervised model trained a labeled source domain. One popular solution is self-training, which retrains with pseudo labels instances. Plenty of approaches tend alleviate noisy labels, however, they ignore intrinsic connection training data, i.e., intra-class compa...

Texture remains largely underutilized in the analysis of remote sensed datasets compared to descriptors based on the orthogonal spectral dimension. This paper describes our recent efforts towards using texture to automate the annotation of remote sensed imagery Two applications are described that use the homogeneous texture descriptor recently standardized by MPEG-7. In the Jirst, higher-level ...

Reflection is common when we see through a glass window, which not only visual disturbance but also influences the performance of computer vision algorithms. Removing reflection from single image, however, highly ill-posed since color at each pixel needs to be separated into two values belonging clear background and reflection, respectively. To solve this, existing methods use additional priors...

Pixel-wise clean annotation is necessary for fully-supervised semantic segmentation, which laborious and expensive to obtain. In this paper, we propose a weakly supervised 2D segmentation model by incorporating sparse bounding box labels with available 3D information, much easier obtain advanced sensors. We introduce 2D-3D inference module generate accurate pixel-wise segment proposal masks. Gu...

Image smoothing is a fundamental low-level vision task that aims to preserve salient structures of an image while removing insignificant details. Deep learning has been explored in deal with the complex entanglement semantic and trivial However, current methods neglect two important facts smoothing: 1) naive pixel-level regression supervised by limited number high-quality ground-truth could lea...