Most existing salient object detection methods mostly use U-Net or feature pyramid structure,
which simply aggregates feature maps of different scales, ignoring the uniqueness and …

Light field salient object detection (LF SOD) has recently received increasing attention.
However, most current works typically rely on an individual focal stack backbone for feature …

Recently, many Light Field Salient Object Detection (LF SOD) methods have been
proposed. However, guaranteeing the integrality and recovering more high-frequency …

Semantic segmentation based on 4D light field (LF) images exhibits superior performance
by exploiting rich spatial and angular information. However, current methods only focus on …

Pixel-level structure segmentations have attracted considerable attention, playing a crucial
role in autonomous driving within the metaverse and enhancing comprehension in light field …

Light field cameras are capable of capturing intricate angular and spatial details. This allows
for acquiring complex light patterns and details from multiple angles, significantly enhancing …

The estimation of depth from 4D light field images is a fundamental problem for perceiving
and reconstructing environmental scenes. While learning-based methods have achieved …

Data augmentation methods are crucial to improve the accuracy of densely occluded object
recognition in the scene where the quantity and diversity of training images are insufficient …

显著目标检测(SOD) 旨在模仿人类视觉系统注意力机制和认知机制来自动提取场景中的显著
物体. 虽然现有基于卷积神经网络(CNN) 或Transformer 的模型不断刷新该领域方法的性能 …

Leveraging the rich information extracted from light field (LF) cameras is instrumental for
dense prediction tasks. However, adapting light field data to enhance Salient Object …