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

Recently AddedMost HypedMost ActiveNeeds VerificationMost Verified

Showing 41–50 of 63 papers

TitleStatusHype
Optimized Hybrid Focal Margin Loss for Crack Segmentation—0
The Devil is in the Crack Orientation: A New Perspective for Crack Detection—0
CrackSeg9k: A Collection and Benchmark for Crack Segmentation Datasets and FrameworksCode1
RHA-Net: An Encoder-Decoder Network with Residual Blocks and Hybrid Attention Mechanisms for Pavement Crack Segmentation—0
Weakly-Supervised Crack Detection—0
Local Intensity Order Transformation for Robust Curvilinear Object SegmentationCode1
What's Cracking? A Review and Analysis of Deep Learning Methods for Structural Crack Segmentation, Detection and Quantification—0
SCNet: A Generalized Attention-based Model for Crack Fault Segmentation—0
Weakly-Supervised Surface Crack Segmentation by Generating Pseudo-Labels using Localization with a Classifier and ThresholdingCode1
Crack Segmentation for Low-Resolution Images using Joint Learning with Super-ResolutionCode1
Show:102550
← PrevPage 5 of 7Next →

No leaderboard results yet.