We address the problem of weakly supervised semantic segmentation. The training images are labeled only by the classes they contain, not by their location in the image. On test im...
Alexander Vezhnevets, Vittorio Ferrari, Joachim M....
This paper presents a novel block-based segmentation and adaptive coding(BSAC) algorithm for visually lossless compression of scanned documents that contain not only photographic ...
K-Nearest Neighbors relies on the definition of a global metric. In contrast, Discriminant Adaptive Nearest Neighbor (DANN) computes a different metric at each query point based o...
This paper proposes a learning scheme based still image super-resolution reconstruction algorithm. Superresolution reconstruction is proposed as a binary classification problem an...
This paper describes an approach to attention based layout segmentation using general principles of the human visual perception to achieve this goal. The text is considered as tex...