Semantic image segmentation, which becomes one of the key applications in image
processing and computer vision domain, has been used in multiple domains such as …

Human pose estimation aims at predicting the poses of human body parts in images or
videos. Since pose motions are often driven by some specific human actions, knowing the …

Modern object detectors rely heavily on rectangular bounding boxes, such as anchors,
proposals and the final predictions, to represent objects at various recognition stages. The …

The Jaccard index, also referred to as the intersection-over-union score, is commonly
employed in the evaluation of image segmentation results given its perceptual qualities …

At the present time photographic visual processing is rapidly moving towards the next stage.
In addition, a variety of visual processing technologies are evolving, such as splitting image …

Recognition algorithms based on convolutional networks (CNNs) typically use the output of
the last layer as feature representation. However, the information in this layer may be too …

We aim to detect all instances of a category in an image and, for each instance, mark the
pixels that belong to it. We call this task Simultaneous Detection and Segmentation (SDS) …

The current dominant paradigm for feature learning in computer vision relies on training
neural networks for the task of object recognition using millions of hand labelled images. Is it …

Object detectors have hugely profited from moving towards an end-to-end learning
paradigm: proposals, fea tures, and the classifier becoming one neural network improved …

Although action recognition in videos is widely studied, current methods often fail on real-
world datasets. Many recent approaches improve accuracy and robustness to cope with …