Real-Time Semantic Segmentation
86 papers with code • 8 benchmarks • 12 datasets
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 )
Benchmarks
These leaderboards are used to track progress in Real-Time Semantic Segmentation
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Libraries
Use these libraries to find Real-Time Semantic Segmentation models and implementationsDatasets
Cityscapes
NYUv2
COCO-Stuff
CamVid
Kvasir-SEG
Kvasir
Kvasir-Instrument
FLAME
Medico automatic polyp segmentation challenge (dataset)
KvasirCapsule-SEG
Latest papers
Doubly Contrastive End-to-End Semantic Segmentation for Autonomous Driving under Adverse Weather
andyj1/doubly-contrastive-semseg
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Road scene understanding tasks have recently become crucial for self-driving vehicles.
MFNet: Multi-Feature Fusion Network for Real-Time Semantic Segmentation in Road Scenes
lu123456789/MFNet
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IEEE Transactions on Intelligent Transportation Systems 2022
Although high-accuracy networks have been applied to semantic segmentation at present, their inference speeds remain slow.
RTFormer: Efficient Design for Real-Time Semantic Segmentation with Transformer
Recently, transformer-based networks have shown impressive results in semantic segmentation.
TriangleNet: Edge Prior Augmented Network for Semantic Segmentation through Cross-Task Consistency
nailperry-zd/paddleseg-trianglenet
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The proposed method underscores the significance of multi-task learning and explicit cross-task consistency enhancement for advancing semantic segmentation and highlights the potential of multitasking in real-time semantic segmentation.
Deep Learning on Home Drone: Searching for the Optimal Architecture
yotamgurfinkel/deeplearningondevice
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We suggest the first system that runs real-time semantic segmentation via deep learning on a weak micro-computer such as the Raspberry Pi Zero v2 (whose price was \$15) attached to a toy-drone.
A Real-time Fire Segmentation Method Based on A Deep Learning Approach
maidacundo/real-time-fire-segmentation-deep-learning
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IFAC-PapersOnLine 2022
Different from deeplabv3+, in order to improve the segmentation speed, this paper uses the lightweight network mobilenetv3 to build a new deep convolutional neural network and does not use atrous convolution, but it will affect the segmentation accuracy.
SFNet: Faster, Accurate, and Domain Agnostic Semantic Segmentation via Semantic Flow
lxtGH/SFSegNets
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In this paper, we focus on exploring effective methods for faster, accurate, and domain agnostic semantic segmentation.
Online Segmentation of LiDAR Sequences: Dataset and Algorithm
Roof-mounted spinning LiDAR sensors are widely used by autonomous vehicles.
S$^2$-FPN: Scale-ware Strip Attention Guided Feature Pyramid Network for Real-time Semantic Segmentation
This paper presents a new model to achieve a trade-off between accuracy/speed for real-time road scene semantic segmentation.
PIDNet: A Real-time Semantic Segmentation Network Inspired by PID Controllers
XuJiacong/PIDNet
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CVPR 2023
To alleviate this problem, we propose a novel three-branch network architecture: PIDNet, which contains three branches to parse detailed, context and boundary information, respectively, and employs boundary attention to guide the fusion of detailed and context branches.
