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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 101125 of 145 papers

TitleStatusHype
ICFRNet: Image Complexity Prior Guided Feature Refinement for Real-time Semantic Segmentation0
Visual Localization Using Semantic Segmentation and Depth Prediction0
Spirit Distillation: Precise Real-time Semantic Segmentation of Road Scenes with Insufficient Data0
Stage-Aware Feature Alignment Network for Real-Time Semantic Segmentation of Street Scenes0
Local-to-Global Information Communication for Real-Time Semantic Segmentation Network Search0
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
Fully Convolutional Networks for Semantic SegmentationCode0
BlitzNet: A Real-Time Deep Network for Scene UnderstandingCode0
Graph-guided Architecture Search for Real-time Semantic SegmentationCode0
P2AT: Pyramid Pooling Axial Transformer for Real-time Semantic SegmentationCode0
Efficient ConvNet for Real-time Semantic SegmentationCode0
DABNet: Depth-wise Asymmetric Bottleneck for Real-time Semantic SegmentationCode0
PointSeg: Real-Time Semantic Segmentation Based on 3D LiDAR Point CloudCode0
Efficient Dense Modules of Asymmetric Convolution for Real-Time Semantic SegmentationCode0
ICNet for Real-Time Semantic Segmentation on High-Resolution ImagesCode0
Incorporating Luminance, Depth and Color Information by a Fusion-based Network for Semantic SegmentationCode0
A Comparative Study of High-Recall Real-Time Semantic Segmentation Based on Swift Factorized NetworkCode0
In Defense of Pre-Trained ImageNet Architectures for Real-Time Semantic Segmentation of Road-Driving ImagesCode0
Uncertainty in Real-Time Semantic Segmentation on Embedded SystemsCode0
LEDNet: A Lightweight Encoder-Decoder Network for Real-Time Semantic SegmentationCode0
Deep Learning on Home Drone: Searching for the Optimal ArchitectureCode0
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