Recent advances in deep learning have enhanced medical imaging research. Breast cancer
is the most prevalent cancer among women, and many applications have been developed to …

Multi-target tracking, a high-level vision job in computer vision, is crucial to understanding
autonomous driving surroundings. Numerous top-notch multi-object tracking algorithms …

It is a challenging task to learn discriminative representation from images and videos, due to
large local redundancy and complex global dependency in these visual data. Convolution …

Semantic segmentation is an extremely challenging task in high-resolution remote sensing
(HRRS) images as objects have complex spatial layouts and enormous variations in …

The performance of crack segmentation is influenced by complex scenes, including
irregularly shaped cracks, complex image backgrounds, and limitations in acquiring global …

Transformers have demonstrated remarkable accomplishments in several natural language
processing (NLP) tasks as well as image processing tasks. Herein, we present a deep …

Road extraction from a remote sensing image is a research hotspot due to its broad range of
applications. Despite recent advancements, achieving precise road extraction remains …

Recently, MLP-Like networks have been revived for image recognition. However, whether it
is possible to build a generic MLP-Like architecture on video domain has not been explored …

Real-time and high-performance semantic segmentation is a crucial task in the scene
understanding of autonomous vehicles. This paper focuses on this issue and proposes a …

Abstract Text-to-image (T2I) generation, which involves synthesizing an image from a textual
description, has emerged as a popular research topic in computer vision. Meanwhile …