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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 110 of 145 papers

TitleStatusHype
PyramidMamba: Rethinking Pyramid Feature Fusion with Selective Space State Model for Semantic Segmentation of Remote Sensing ImageryCode5
Golden Cudgel Network for Real-Time Semantic SegmentationCode2
DSNet: A Novel Way to Use Atrous Convolutions in Semantic SegmentationCode2
A Multi-objective Optimization Benchmark Test Suite for Real-time Semantic SegmentationCode2
SCTNet: Single-Branch CNN with Transformer Semantic Information for Real-Time SegmentationCode2
SegNeXt: Rethinking Convolutional Attention Design for Semantic SegmentationCode2
SFNet: Faster, Accurate, and Domain Agnostic Semantic Segmentation via Semantic FlowCode2
PIDNet: A Real-time Semantic Segmentation Network Inspired by PID ControllersCode2
BiSeNet V2: Bilateral Network with Guided Aggregation for Real-time Semantic SegmentationCode2
SOLOv2: Dynamic and Fast Instance SegmentationCode2
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