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 6170 of 145 papers

TitleStatusHype
Fast-SCNN: Fast Semantic Segmentation NetworkCode0
A Comparative Study of High-Recall Real-Time Semantic Segmentation Based on Swift Factorized NetworkCode0
FasterSeg: Searching for Faster Real-time Semantic SegmentationCode0
DABNet: Depth-wise Asymmetric Bottleneck for Real-time Semantic SegmentationCode0
PointSeg: Real-Time Semantic Segmentation Based on 3D LiDAR Point CloudCode0
ESPNetv2: A Light-weight, Power Efficient, and General Purpose Convolutional Neural NetworkCode0
ESPNet: Efficient Spatial Pyramid of Dilated Convolutions for Semantic SegmentationCode0
ERFNet: Efficient Residual Factorized ConvNet for Real-time Semantic SegmentationCode0
P2AT: Pyramid Pooling Axial Transformer for Real-time Semantic SegmentationCode0
COVERED, CollabOratiVE Robot Environment Dataset for 3D Semantic segmentationCode0
Show:102550
← PrevPage 7 of 15Next →

No leaderboard results yet.