The ability to predict, anticipate and reason about future outcomes is a key component of
intelligent decision-making systems. In light of the success of deep learning in computer …

Pixel-wise regression is probably the most common problem in fine-grained computer vision
tasks, such as estimating keypoint heatmaps and segmentation masks. These regression …

High-resolution representations are essential for position-sensitive vision problems, such as
human pose estimation, semantic segmentation, and object detection. Existing state-of-the …

Image segmentation is the task of associating pixels in an image with their respective object
class labels. It has a wide range of applications in many industries including healthcare …

High-resolution representation learning plays an essential role in many vision problems, eg,
pose estimation and semantic segmentation. The high-resolution network (HRNet)~\cite …

We notice information flow in convolutional neural networks is restricted inside local
neighborhood regions due to the physical design of convolutional filters, which limits the …

Semantic image segmentation is a basic street scene understanding task in autonomous
driving, where each pixel in a high resolution image is categorized into a set of semantic …

In this paper, we present a new large-scale dataset for the video panoptic segmentation
task, which aims to assign semantic classes and track identities to all pixels in a video. As …

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 …

We address the pixel-wise mapping problem that commonly exists in the fine-grained
computer vision tasks, such as estimating keypoint heatmaps and segmentation masks …