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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 71–80 of 145 papers

TitleStatusHype
Bilateral attention decoder: A lightweight decoder for real-time semantic segmentation—0
Deep Dual-resolution Networks for Real-time and Accurate Semantic Segmentation of Road ScenesCode1
DDANet: Dual Decoder Attention Network for Automatic Polyp SegmentationCode1
HyperSeg: Patch-wise Hypernetwork for Real-time Semantic SegmentationCode1
SegBlocks: Block-Based Dynamic Resolution Networks for Real-Time SegmentationCode1
Real-Time Polyp Detection, Localization and Segmentation in Colonoscopy Using Deep LearningCode1
Multi Projection Fusion for Real-time Semantic Segmentation of 3D LiDAR Point Clouds—0
Real-time Semantic Segmentation with Context Aggregation Network—0
Dense Dual-Path Network for Real-time Semantic Segmentation—0
Multi-scale Interaction for Real-time LiDAR Data Segmentation on an Embedded PlatformCode1
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