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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 91–100 of 145 papers

TitleStatusHype
Real-time semantic segmentation on FPGAs for autonomous vehicles with hls4ml—0
Entropy-Based Feature Extraction For Real-Time Semantic Segmentation—0
ESNet: An Efficient Symmetric Network for Real-time Semantic Segmentation—0
FarSee-Net: Real-Time Semantic Segmentation by Efficient Multi-scale Context Aggregation and Feature Space Super-resolution—0
Real-Time Semantic Segmentation via Auto Depth, Downsampling Joint Decision and Feature Aggregation—0
Feature Pyramid Encoding Network for Real-time Semantic Segmentation—0
Guided Upsampling Network for Real-Time Semantic Segmentation—0
Real-Time Semantic Segmentation via Multiply Spatial Fusion Network—0
Tamed Warping Network for High-Resolution Semantic Video Segmentation—0
AASeg: Attention Aware Network for Real Time Semantic Segmentation—0
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