Real-Time Semantic Segmentation
64 papers with code • 5 benchmarks • 10 datasets
Real-time semantic segmentation is the task of achieving computationally efficient semantic segmentation (while maintaining a base level of accuracy).
( 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
CamVid
COCO-Stuff
Kvasir-SEG
Kvasir
Kvasir-Instrument
Medico automatic polyp segmentation challenge (dataset)
KvasirCapsule-SEG
Endotect Polyp Segmentation Challenge Dataset
Most implemented papers
SegNet: A Deep Convolutional Encoder-Decoder Architecture for Image Segmentation
We show that SegNet provides good performance with competitive inference time and more efficient inference memory-wise as compared to other architectures.
Pyramid Scene Parsing Network
Scene parsing is challenging for unrestricted open vocabulary and diverse scenes.
ENet: A Deep Neural Network Architecture for Real-Time Semantic Segmentation
The ability to perform pixel-wise semantic segmentation in real-time is of paramount importance in mobile applications.
Fully Convolutional Networks for Semantic Segmentation
Convolutional networks are powerful visual models that yield hierarchies of features.
Fast-SCNN: Fast Semantic Segmentation Network
The encoder-decoder framework is state-of-the-art for offline semantic image segmentation.
HarDNet: A Low Memory Traffic Network
PingoLH/Pytorch-HarDNet
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ICCV 2019
We propose a Harmonic Densely Connected Network to achieve high efficiency in terms of both low MACs and memory traffic.
Semantic Image Segmentation with Deep Convolutional Nets and Fully Connected CRFs
This is due to the very invariance properties that make DCNNs good for high level tasks.
BiSeNet: Bilateral Segmentation Network for Real-time Semantic Segmentation
PaddlePaddle/PaddleSeg
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ECCV 2018
Semantic segmentation requires both rich spatial information and sizeable receptive field.
SOLOv2: Dynamic and Fast Instance Segmentation
WXinlong/SOLO
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NeurIPS 2020
Importantly, we take one step further by dynamically learning the mask head of the object segmenter such that the mask head is conditioned on the location.
ICNet for Real-Time Semantic Segmentation on High-Resolution Images
We focus on the challenging task of real-time semantic segmentation in this paper.
