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
DABNet: Depth-wise Asymmetric Bottleneck for Real-time Semantic SegmentationCode0
A Comparative Study of High-Recall Real-Time Semantic Segmentation Based on Swift Factorized NetworkCode0
ESNet: An Efficient Symmetric Network for Real-time Semantic Segmentation—0
DiCENet: Dimension-wise Convolutions for Efficient NetworksCode0
In Defense of Pre-Trained ImageNet Architectures for Real-Time Semantic Segmentation of Road-Driving ImagesCode0
LEDNet: A Lightweight Encoder-Decoder Network for Real-Time Semantic SegmentationCode0
MAVNet: an Effective Semantic Segmentation Micro-Network for MAV-based TasksCode0
DFANet: Deep Feature Aggregation for Real-Time Semantic SegmentationCode0
Fast-SCNN: Fast Semantic Segmentation NetworkCode0
Random Forest with Learned Representations for Semantic Segmentation—0
Show:102550
← PrevPage 12 of 15Next →

No leaderboard results yet.