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

Showing 7180 of 145 papers

TitleStatusHype
LEDNet: A Lightweight Encoder-Decoder Network for Real-Time Semantic SegmentationCode0
Feature Reuse and Fusion for Real-time Semantic segmentationCode0
DFANet: Deep Feature Aggregation for Real-Time Semantic SegmentationCode0
DiCENet: Dimension-wise Convolutions for Efficient NetworksCode0
Doubly Contrastive End-to-End Semantic Segmentation for Autonomous Driving under Adverse WeatherCode0
Light-Weight RefineNet for Real-Time Semantic SegmentationCode0
TriangleNet: Edge Prior Augmented Network for Semantic Segmentation through Cross-Task ConsistencyCode0
Efficient ConvNet for Real-time Semantic SegmentationCode0
Efficient Dense Modules of Asymmetric Convolution for Real-Time Semantic SegmentationCode0
P2AT: Pyramid Pooling Axial Transformer for Real-time Semantic SegmentationCode0
Show:102550
← PrevPage 8 of 15Next →

No leaderboard results yet.