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 8190 of 145 papers

TitleStatusHype
LiteSeg: A Novel Lightweight ConvNet for Semantic SegmentationCode0
Fast-SCNN: Fast Semantic Segmentation NetworkCode0
Full-Resolution Residual Networks for Semantic Segmentation in Street ScenesCode0
PointSeg: Real-Time Semantic Segmentation Based on 3D LiDAR Point CloudCode0
Fully Convolutional Networks for Semantic SegmentationCode0
BlitzNet: A Real-Time Deep Network for Scene UnderstandingCode0
Uncertainty in Real-Time Semantic Segmentation on Embedded SystemsCode0
ERFNet: Efficient Residual Factorized ConvNet for Real-time Semantic SegmentationCode0
MAVNet: an Effective Semantic Segmentation Micro-Network for MAV-based TasksCode0
ESPNet: Efficient Spatial Pyramid of Dilated Convolutions for Semantic SegmentationCode0
Show:102550
← PrevPage 9 of 15Next →

No leaderboard results yet.