We propose a performance evaluation method of real-time semantic segmentation models to compare the performance under the same conditions fairly.
Dec 28, 2022 · We compare the performance of real-time semantic segmentation models with non-real-time counterparts constrained by aerial images under ...
A performance evaluation method of real-time semantic segmentation models is proposed to compare the performance under the same conditions fairly and the ...
In this paper, we propose a model that can generate stereo images from a single image, considering both translation as well as rotation of objects in the image.
We propose AutoSegEdge, based on Neural Architecture Search (NAS), a semantic segmentation approach that runs on edge devices in real-time.
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However, there is still a significant gap in performance between these real-time methods and the models based on dilation backbones. To this end, we ...
The research in real-time segmentation mainly focuses on desktop GPUs. However, autonomous driving and many other applications rely on real-time ...
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In this study, we trained and evaluated four real-time semantic segmentation models and three object detection models specifically for aphid cluster ...
This review provides an in-depth analysis of state-of-the-art approaches in real-time semantic segmentation, with a particular focus on Convolutional Neural ...
Although existing real-time semantic segmentation models achieve a commendable balance between accuracy and speed, their multi-path blocks still affect overall ...
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