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 with no code
Entropy-Based Feature Extraction For Real-Time Semantic Segmentation
Patches with high entropy are being processed by the encoder with the largest number of parameters, patches with moderate entropy are processed by the encoder with a moderate number of parameters, and patches with low entropy are processed by the smallest encoder.
On Efficient Real-Time Semantic Segmentation: A Survey
Semantic segmentation is the problem of assigning a class label to every pixel in an image, and is an important component of an autonomous vehicle vision stack for facilitating scene understanding and object detection.
Real-time semantic segmentation on FPGAs for autonomous vehicles with hls4ml
In this paper, we investigate how field programmable gate arrays can serve as hardware accelerators for real-time semantic segmentation tasks relevant for autonomous driving.
Deep Multi-Branch Aggregation Network for Real-Time Semantic Segmentation in Street Scenes
This shows that DMA-Net provides a good tradeoff between segmentation quality and speed for semantic segmentation in street scenes.
Stage-Aware Feature Alignment Network for Real-Time Semantic Segmentation of Street Scenes
In this paper, we present a novel Stage-aware Feature Alignment Network (SFANet) based on the encoder-decoder structure for real-time semantic segmentation of street scenes.
Boundary Corrected Multi-scale Fusion Network for Real-time Semantic Segmentation
Image semantic segmentation aims at the pixel-level classification of images, which has requirements for both accuracy and speed in practical application.
A-Eye: Driving with the Eyes of AI for Corner Case Generation
For the test rig, a real-time semantic segmentation network is trained and integrated into the driving simulation software CARLA in such a way that a human can drive on the network's prediction.
AASeg: Attention Aware Network for Real Time Semantic Segmentation
In this paper, we present a new network named Attention Aware Network (AASeg) for real time semantic image segmentation.
Real Time Egocentric Object Segmentation: THU-READ Labeling and Benchmarking Results
Egocentric segmentation has attracted recent interest in the computer vision community due to their potential in Mixed Reality (MR) applications.
CSRNet: Cascaded Selective Resolution Network for Real-time Semantic Segmentation
Real-time semantic segmentation has received considerable attention due to growing demands in many practical applications, such as autonomous vehicles, robotics, etc.
