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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 11–20 of 145 papers

TitleStatusHype
A New Dataset and Comparative Study for Aphid Cluster Detection and Segmentation in Sorghum Fields—0
A Multi-objective Optimization Benchmark Test Suite for Real-time Semantic SegmentationCode2
SwinMTL: A Shared Architecture for Simultaneous Depth Estimation and Semantic Segmentation from Monocular Camera ImagesCode1
Multi-Level Aggregation and Recursive Alignment Architecture for Efficient Parallel Inference Segmentation NetworkCode0
SCTNet: Single-Branch CNN with Transformer Semantic Information for Real-Time SegmentationCode2
MCFNet: Multi-scale Covariance Feature Fusion Network for Real-time Semantic Segmentation—0
Mobile-Seed: Joint Semantic Segmentation and Boundary Detection for Mobile RobotsCode1
Bilateral Network with Residual U-blocks and Dual-Guided Attention for Real-time Semantic SegmentationCode1
P2AT: Pyramid Pooling Axial Transformer for Real-time Semantic SegmentationCode0
AsymFormer: Asymmetrical Cross-Modal Representation Learning for Mobile Platform Real-Time RGB-D Semantic SegmentationCode1
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