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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 61–70 of 145 papers

TitleStatusHype
Dense Dual-Path Network for Real-time Semantic Segmentation—0
Guided Upsampling Network for Real-Time Semantic Segmentation—0
Bilateral attention decoder: A lightweight decoder for real-time semantic segmentation—0
On Efficient Real-Time Semantic Segmentation: A Survey—0
AASeg: Attention Aware Network for Real Time Semantic Segmentation—0
Multi Projection Fusion for Real-time Semantic Segmentation of 3D LiDAR Point Clouds—0
ESNet: An Efficient Symmetric Network for Real-time Semantic Segmentation—0
CSRNet: Cascaded Selective Resolution Network for Real-time Semantic Segmentation—0
Entropy-Based Feature Extraction For Real-Time Semantic Segmentation—0
Cross-CBAM: A Lightweight network for Scene Segmentation—0
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