SOTAVerified

Crack Segmentation

Crack segmentation in computer vision involves identifying and delineating cracks or fractures in various types of surfaces, such as roads, pavements, walls, or infrastructure. This task is crucial for infrastructure maintenance, as it helps in assessing the condition of structures and planning repairs.

Papers

Showing 3140 of 63 papers

TitleStatusHype
FlexiCrackNet: A Flexible Pipeline for Enhanced Crack Segmentation with General Features Transfered from SAM0
What's Cracking? A Review and Analysis of Deep Learning Methods for Structural Crack Segmentation, Detection and Quantification0
Vision Mamba-based autonomous crack segmentation on concrete, asphalt, and masonry surfaces0
Automated Pavement Crack Segmentation Using U-Net-based Convolutional Neural Network0
The Devil is in the Crack Orientation: A New Perspective for Crack Detection0
Weakly-Supervised Crack Detection0
Joint Super-Resolution and Rectification for Solar Cell Inspection0
A statistical method for crack detection in 3D concrete images0
TrueDeep: A systematic approach of crack detection with less data0
A Deep Neural Networks Approach for Pixel-Level Runway Pavement Crack Segmentation Using Drone-Captured Images0
Show:102550
← PrevPage 4 of 7Next →

No leaderboard results yet.