Image instance segmentation involves labeling pixels of images with classes and instances,
which is one of the pivotal technologies in many domains, such as natural scenes …

Artificial vision has often been described as one of the key remaining challenges to be
solved before machines can act intelligently. Recent developments in a branch of machine …

We design an open-vocabulary image segmentation model to organize an image into
meaningful regions indicated by arbitrary texts. Recent works (CLIP and ALIGN), despite …

Instance segmentation is a fundamental vision task that aims to recognize and segment
each object in an image. However, it requires costly annotations such as bounding boxes …

We explore the potential of pooling techniques on the task of salient object detection by
expanding its role in convolutional neural networks. In general, two pooling-based modules …

Automatic pavement crack segmentation plays a critical role in the field of defect inspection.
Although recent segmentation-based CNNs studies showed a promising pavement crack …

Exploiting multi-scale representations is critical to improve edge detection for objects at
different scales. To extract edges at dramatically different scales, we propose a Bi …

In this paper, we argue about the importance of considering task interactions at multiple
scales when distilling task information in a multi-task learning setup. In contrast to common …

This paper explores the use of extreme points in an object (left-most, right-most, top, bottom
pixels) as input to obtain precise object segmentation for images and videos. We do so by …

In this work we address task interference in universal networks by considering that a network
is trained on multiple tasks, but performs one task at a time, an approach we refer to as" …