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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

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Showing 1–25 of 145 papers

TitleStatusHype
PyramidMamba: Rethinking Pyramid Feature Fusion with Selective Space State Model for Semantic Segmentation of Remote Sensing ImageryCode5
PIDNet: A Real-time Semantic Segmentation Network Inspired by PID ControllersCode2
SOLOv2: Dynamic and Fast Instance SegmentationCode2
SegNeXt: Rethinking Convolutional Attention Design for Semantic SegmentationCode2
BiSeNet V2: Bilateral Network with Guided Aggregation for Real-time Semantic SegmentationCode2
SCTNet: Single-Branch CNN with Transformer Semantic Information for Real-Time SegmentationCode2
DSNet: A Novel Way to Use Atrous Convolutions in Semantic SegmentationCode2
SFNet: Faster, Accurate, and Domain Agnostic Semantic Segmentation via Semantic FlowCode2
Golden Cudgel Network for Real-Time Semantic SegmentationCode2
A Multi-objective Optimization Benchmark Test Suite for Real-time Semantic SegmentationCode2
Lightweight Real-time Semantic Segmentation Network with Efficient Transformer and CNNCode1
Bilateral Network with Residual U-blocks and Dual-Guided Attention for Real-time Semantic SegmentationCode1
BiSeNet: Bilateral Segmentation Network for Real-time Semantic SegmentationCode1
In Defense of Pre-trained ImageNet Architectures for Real-time Semantic Segmentation of Road-driving ImagesCode1
JetSeg: Efficient Real-Time Semantic Segmentation Model for Low-Power GPU-Embedded SystemsCode1
Lite-HRNet: A Lightweight High-Resolution NetworkCode1
Real-time Semantic Segmentation via Spatial-detail Guided Context PropagationCode1
Deep Dual-resolution Networks for Real-time and Accurate Semantic Segmentation of Road ScenesCode1
3D-MiniNet: Learning a 2D Representation from Point Clouds for Fast and Efficient 3D LIDAR Semantic SegmentationCode1
FEANet: Feature-Enhanced Attention Network for RGB-Thermal Real-time Semantic SegmentationCode1
HarDNet: A Low Memory Traffic NetworkCode1
DDANet: Dual Decoder Attention Network for Automatic Polyp SegmentationCode1
CFPNet: Channel-wise Feature Pyramid for Real-Time Semantic SegmentationCode1
CSFNet: A Cosine Similarity Fusion Network for Real-Time RGB-X Semantic Segmentation of Driving ScenesCode1
AsymFormer: Asymmetrical Cross-Modal Representation Learning for Mobile Platform Real-Time RGB-D Semantic SegmentationCode1
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