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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 101–110 of 145 papers

TitleStatusHype
ICFRNet: Image Complexity Prior Guided Feature Refinement for Real-time Semantic Segmentation—0
Visual Localization Using Semantic Segmentation and Depth Prediction—0
Spirit Distillation: Precise Real-time Semantic Segmentation of Road Scenes with Insufficient Data—0
Stage-Aware Feature Alignment Network for Real-Time Semantic Segmentation of Street Scenes—0
Local-to-Global Information Communication for Real-Time Semantic Segmentation Network Search—0
ShuffleSeg: Real-time Semantic Segmentation NetworkCode0
ESPNet: Efficient Spatial Pyramid of Dilated Convolutions for Semantic SegmentationCode0
ESPNetv2: A Light-weight, Power Efficient, and General Purpose Convolutional Neural NetworkCode0
Feature Reuse and Fusion for Real-time Semantic segmentationCode0
Full-Resolution Residual Networks for Semantic Segmentation in Street ScenesCode0
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