Augmented Reality (AR) is an augmented depiction of reality formed by overlaying digital
information on an image of objects being seen through a device. Artificial Intelligence (AI) …

With the rapid development of deep learning techniques, deep convolutional neural
networks (DCNNs) have become more important for object detection. Compared with …

With the rapid development of object detection, it is widely used in many scenes and
images. However, the dense arrangement of objects with different dimensions, orientations …

Video segmentation—partitioning video frames into multiple segments or objects—plays a
critical role in a broad range of practical applications, from enhancing visual effects in movie …

In this paper, we present a novel end-to-end learning neural network, ie, MATNet, for zero-
shot video object segmentation (ZVOS). Motivated by the human visual attention behavior …

Object detection, one of the most fundamental and challenging problems in computer vision,
seeks to locate object instances from a large number of predefined categories in natural …

Contemporary neural networks still fall short of human-level generalization, which extends
far beyond our direct experiences. In this paper, we argue that the underlying cause for this …

Fine-grained classification is challenging due to the difficulty of finding discriminative
features. Finding those subtle traits that fully characterize the object is not straightforward. To …

The field of object detection has made significant advances riding on the wave of region-
based ConvNets, but their training procedure still includes many heuristics and …

In the last few years, deep learning has led to very good performance on a variety of
problems, such as visual recognition, speech recognition and natural language processing …