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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

Showing 5160 of 145 papers

TitleStatusHype
Bilateral Network with Residual U-blocks and Dual-Guided Attention for Real-time Semantic SegmentationCode1
SegNet: A Deep Convolutional Encoder-Decoder Architecture for Image SegmentationCode1
DDANet: Dual Decoder Attention Network for Automatic Polyp SegmentationCode1
A Comparative Study of High-Recall Real-Time Semantic Segmentation Based on Swift Factorized NetworkCode0
Fully Convolutional Networks for Semantic SegmentationCode0
Full-Resolution Residual Networks for Semantic Segmentation in Street ScenesCode0
Feature Reuse and Fusion for Real-time Semantic segmentationCode0
Deep Learning on Home Drone: Searching for the Optimal ArchitectureCode0
Multi-Scale Context Aggregation by Dilated ConvolutionsCode0
Fast-SCNN: Fast Semantic Segmentation NetworkCode0
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