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 111–120 of 145 papers

TitleStatusHype
Tamed Warping Network for High-Resolution Semantic Video Segmentation—0
AASeg: Attention Aware Network for Real Time Semantic Segmentation—0
ICFRNet: Image Complexity Prior Guided Feature Refinement for Real-time Semantic Segmentation—0
Visual Localization Using Semantic Segmentation and Depth Prediction—0
Spirit Distillation: Precise Real-time Semantic Segmentation of Road Scenes with Insufficient Data—0
Stage-Aware Feature Alignment Network for Real-Time Semantic Segmentation of Street Scenes—0
Local-to-Global Information Communication for Real-Time Semantic Segmentation Network Search—0
Lookahead Adversarial Learning for Near Real-Time Semantic Segmentation—0
LRNNet: A Light-Weighted Network with Efficient Reduced Non-Local Operation for Real-Time Semantic Segmentation—0
MCFNet: Multi-scale Covariance Feature Fusion Network for Real-time Semantic Segmentation—0
Show:102550
← PrevPage 12 of 15Next →

No leaderboard results yet.