Semantic segmentation is the pixel-wise labeling of an image. Boosted by the extraordinary
ability of convolutional neural networks (CNN) in creating semantic, high-level and …

Semantic segmentation, also called scene labeling, refers to the process of assigning a
semantic label (eg car, people, and road) to each pixel of an image. It is an essential data …

Prevalent semantic segmentation solutions, despite their different network designs (FCN
based or attention based) and mask decoding strategies (parametric softmax based or pixel …

Processing point cloud data is an important component of many real-world systems. As
such, a wide variety of point-based approaches have been proposed, reporting steady …

From the autonomous car driving to medical diagnosis, the requirement of the task of image
segmentation is everywhere. Segmentation of an image is one of the indispensable tasks in …

Annotating images with pixel-wise labels is a time-consuming and costly process. Recently,
DatasetGAN showcased a promising alternative-to synthesize a large labeled dataset via a …

Semantic classes can be either things (objects with a well-defined shape, eg car, person) or
stuff (amorphous background regions, eg grass, sky). While lots of classification and …

Recent progress in computer vision has been driven by high-capacity models trained on
large datasets. Unfortunately, creating large datasets with pixel-level labels has been …

Semantic segmentation is a challenging task in computer vision systems. A lot of methods
have been developed to tackle this problem ranging from autonomous vehicles, human …

Visual understanding of complex urban street scenes is an enabling factor for a wide range
of applications. Object detection has benefited enormously from large-scale datasets …