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Real-Time Semantic Segmentation

Semantic Segmentation is a computer vision task that involves assigning a semantic label to each pixel in an image. In Real-Time Semantic Segmentation, the goal is to perform this labeling quickly and accurately in real-time, allowing for the segmentation results to be used for tasks such as object recognition, scene understanding, and autonomous navigation.

( Image credit: TorchSeg )

Papers

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Showing 81–90 of 145 papers

TitleStatusHype
Deep Multi-Branch Aggregation Network for Real-Time Semantic Segmentation in Street Scenes—0
Design of Real-time Semantic Segmentation Decoder for Automated Driving—0
Boundary Corrected Multi-scale Fusion Network for Real-time Semantic Segmentation—0
DWRSeg: Rethinking Efficient Acquisition of Multi-scale Contextual Information for Real-time Semantic Segmentation—0
Efficient Joint-Dimensional Search with Solution Space Regularization for Real-Time Semantic Segmentation—0
Efficient Road Lane Marking Detection with Deep Learning—0
Efficient Semantic Segmentation on Edge Devices—0
Efficient Semantic Segmentation using Gradual Grouping—0
Efficient Semantic Segmentation via Lightweight Multiple-Information Interaction Network—0
Efficient Video Semantic Segmentation with Labels Propagation and Refinement—0
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