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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 51–60 of 145 papers

TitleStatusHype
Stage-Aware Feature Alignment Network for Real-Time Semantic Segmentation of Street Scenes—0
Boundary Corrected Multi-scale Fusion Network for Real-time Semantic Segmentation—0
A-Eye: Driving with the Eyes of AI for Corner Case Generation—0
On the Real-World Adversarial Robustness of Real-Time Semantic Segmentation Models for Autonomous DrivingCode1
Rethinking Dilated Convolution for Real-time Semantic SegmentationCode1
Reimagine BiSeNet for Real-Time Domain Adaptation in Semantic SegmentationCode1
FEANet: Feature-Enhanced Attention Network for RGB-Thermal Real-time Semantic SegmentationCode1
FBSNet: A Fast Bilateral Symmetrical Network for Real-Time Semantic SegmentationCode1
AASeg: Attention Aware Network for Real Time Semantic Segmentation—0
Real Time Egocentric Object Segmentation: THU-READ Labeling and Benchmarking Results—0
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