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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 41–50 of 145 papers

TitleStatusHype
A Real-time Fire Segmentation Method Based on A Deep Learning ApproachCode1
SFNet: Faster, Accurate, and Domain Agnostic Semantic Segmentation via Semantic FlowCode2
Entropy-Based Feature Extraction For Real-Time Semantic Segmentation—0
On Efficient Real-Time Semantic Segmentation: A Survey—0
Online Segmentation of LiDAR Sequences: Dataset and AlgorithmCode1
S^2-FPN: Scale-ware Strip Attention Guided Feature Pyramid Network for Real-time Semantic SegmentationCode1
PIDNet: A Real-time Semantic Segmentation Network Inspired by PID ControllersCode2
Real-time semantic segmentation on FPGAs for autonomous vehicles with hls4ml—0
PP-LiteSeg: A Superior Real-Time Semantic Segmentation ModelCode0
Deep Multi-Branch Aggregation Network for Real-Time Semantic Segmentation in Street Scenes—0
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