In this paper, we propose a deep neural network architecture, Multi-Path Fusion Network (MPFNet), for semantic image segmentation. In MPFNet, we add more ...
It is widely used in many computer vision tasks such as street scene recognition, object detection, autonomous driving, scene understanding, robot visi- on. The ...
This paper proposes a deep neural network architecture, Multi-Path Fusion Network (MPFNet), for semantic image segmentation, which improves strong baselines ...
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In this paper, we propose a multipath feature fusion convolutional neural network (MF2-Net) with novel and efficient spatial group convolution (SGC) modules.
Jun 3, 2023 · Common image segmentation methods based on region include the region splitting and merging technique, as well as the region growing technique [7] ...
This paper describes the essential background concepts of deep multimodal fusion and the relevant applications in computer vision.
In order to enhance the segmentation accuracy of brain tissue, this paper proposed an object region segmentation algorithm that combines pixel-level information ...
In this paper, we propose a multipath feature fusion convolutional neural network (MF2-Net) with novel and efficient spatial group convolution (SGC) modules ...
Dec 12, 2024 · In this paper, we propose a multi-path semantic segmentation network with convolutional attention guidance (dubbed MCAG). It has a multi-path ...
The multi-level feature fusion method is well known to contain more spatial information in low-level feature maps, whereas high-level feature maps are richer in ...