Image segmentation is a key task in computer vision and image processing with important
applications such as scene understanding, medical image analysis, robotic perception …

The semantic image segmentation task consists of classifying each pixel of an image into an
instance, where each instance corresponds to a class. This task is a part of the concept of …

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

Self-attention mechanism has been widely used for various tasks. It is designed to compute
the representation of each position by a weighted sum of the features at all positions. Thus, it …

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

Abstract Recently, Neural Architecture Search (NAS) has successfully identified neural
network architectures that exceed human designed ones on large-scale image …

Semantic segmentation is a challenging task in computer vision. In recent years, the
performance of semantic segmentation has been greatly improved by using deep learning …

In this paper, we address the scene segmentation task by capturing rich contextual
dependencies based on the self-attention mechanism. Unlike previous works that capture …

We present a novel, real-time, semantic segmentation network in which the encoder both
encodes and generates the parameters (weights) of the decoder. Furthermore, to allow …

Recent work has shown that depth estimation from a stereo pair of images can be
formulated as a supervised learning task to be resolved with convolutional neural networks …