In this paper, we design a simple yet powerful deep network architecture, U 2-Net, for salient
object detection (SOD). The architecture of our U 2-Net is a two-level nested U-structure. The …

Scene text detection, an important step of scene text reading systems, has witnessed rapid
development with convolutional neural networks. Nonetheless, two main challenges still …

The increasing popularity of attention mechanisms in deep learning algorithms for computer
vision and natural language processing made these models attractive to other research …

This paper is on highly accurate and highly efficient human pose estimation. Recent works
based on Fully Convolutional Networks (FCNs) have demonstrated excellent results for this …

Single-person human pose estimation facilitates markerless movement analysis in sports, as
well as in clinical applications. Still, state-of-the-art models for human pose estimation …

Automatic polyp segmentation has proven to be immensely helpful for endoscopy
procedures, reducing the missing rate of adenoma detection for endoscopists while …

We investigate learning feature-to-feature translator networks by alternating back-
propagation as a general-purpose solution to zero-shot learning (ZSL) problems. It is a …

Artificial neural networks have been shown significant performance in various image-to-
image conversion tasks. However, complex conversions often require a large number of …

We consider the problem of image-to-video translation, where an input image is translated
into an output video containing motions of a single object. Recent methods for such …

In recent years, computer-aided automatic polyp segmentation and neoplasm detection
have been an emerging topic in medical image analysis, providing valuable support to …