Video object segmentation (VOS) aims at segmenting a particular object throughout the
entire video clip sequence. The state-of-the-art VOS methods have achieved excellent …

We propose a Vision-Language Transformer (VLT) framework for referring segmentation to
facilitate deep interactions among multi-modal information and enhance the holistic …

In the field of visual scene understanding, deep neural networks have made impressive
advancements in various core tasks like segmentation, tracking, and detection. However …

The deep CNNs in image semantic segmentation typically require a large number of
densely-annotated images for training and have difficulties in generalizing to unseen object …

Referring segmentation aims to generate a segmentation mask for the target instance
indicated by a natural language expression. There are typically two kinds of existing …

Image matting has attracted growing interest in recent years for its wide applications in
numerous vision tasks. Most previous image matting methods rely on trimaps as auxiliary …

Deep learning techniques have shown their superior performance in dermatologist clinical
inspection. Nevertheless, melanoma diagnosis is still a challenging task due to the difficulty …

This work aims to estimate 6Dof (6D) object pose in background clutter. Considering the
strong occlusion and background noise, we propose to utilize the spatial structure for better …

Referring image segmentation is guided by natural language descriptions to separate the
target objects in an image. This task is different from semantic segmentation and instance …

This work presents a comprehensive exploration of Reverse Engineering of Deceptions
(RED) in the field of adversarial machine learning. It delves into the intricacies of machine …