SOTAVerified

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

Recently AddedMost HypedMost ActiveNeeds VerificationMost Verified

Showing 51–60 of 145 papers

TitleStatusHype
Pyramid Scene Parsing NetworkCode1
ENet: A Deep Neural Network Architecture for Real-Time Semantic SegmentationCode1
SegNet: A Deep Convolutional Encoder-Decoder Architecture for Image SegmentationCode1
Real-Time Semantic Segmentation of Aerial Images Using an Embedded U-Net: A Comparison of CPU, GPU, and FPGA Workflows—0
ContextFormer: Redefining Efficiency in Semantic Segmentation—0
Efficient Semantic Segmentation via Lightweight Multiple-Information Interaction Network—0
ICFRNet: Image Complexity Prior Guided Feature Refinement for Real-time Semantic Segmentation—0
A New Dataset and Comparative Study for Aphid Cluster Detection and Segmentation in Sorghum Fields—0
Multi-Level Aggregation and Recursive Alignment Architecture for Efficient Parallel Inference Segmentation NetworkCode0
MCFNet: Multi-scale Covariance Feature Fusion Network for Real-time Semantic Segmentation—0
Show:102550
← PrevPage 6 of 15Next →

No leaderboard results yet.