显著性目标检测旨在对图像中最显著的对象进行检测和分割, 是计算机视觉任务中重要的预处理
步骤之一, 且在信息检索, 公共安全等领域均有广泛的应用. 本文对近期基于深度学习的显著性 …

As the road traffic situation becomes complex, the task of traffic management takes on an
increasingly heavy load. The air-to-ground traffic administration network of drones has …

Weakly supervised salient object detection (SOD) is a challenging task and has drawn much
attention from several research perspectives, it has revealed two problems while driving the …

Benefiting from deep learning, Salient Object Detection (SOD) has made much progress.
However, most existing methods adopt the same strategy to extract salient cues from …

Vision transformers have been demonstrated to yield state-of-the-art results on a variety of
computer vision tasks using attention-based networks. However, research works in …

The epidemic of gun violence worldwide necessitates the need for an active-based video
surveillance network to combat this crime. In this context, autonomously detecting handguns …

Deep convolutional neural networks have gained aggressive success in salient object
detection. This paper uses the Multi-Scale Feature Extraction Module (MFEM) for each …

Multimodal salient object detection (MSOD), which utilizes multimodal information (eg, RGB
image and thermal infrared or depth image) to detect common salient objects, has received …

The increasing concerns of public health and safety lead to a practical need to detect
smoking behaviors (or smokers) in public places. Previous smoker detection methods often …

Salient object detection (SOD) is a challenging and fundamental research in computer
vision and image processing. Since the cost of pixel-level annotations is high, scribble …