SOTAVerified

Horizon Line Estimation

Papers

Showing 17 of 7 papers

TitleStatusHype
Deep Learning for Vanishing Point Detection Using an Inverse Gnomonic ProjectionCode1
Hinge-Wasserstein: Estimating Multimodal Aleatoric Uncertainty in Regression TasksCode0
Temporally Consistent Horizon LinesCode0
Neural-Guided RANSAC: Learning Where to Sample Model HypothesesCode0
A-Contrario Horizon-First Vanishing Point Detection Using Second-Order Grouping LawsCode0
Detecting Vanishing Points using Global Image Context in a Non-Manhattan WorldCode0
Horizon Lines in the WildCode0
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Benchmark Results

#ModelMetricClaimedVerifiedStatus
1NG-DSACAUC (horizon error)75.2Unverified
2GoogleNet (Huber Loss, horizon line projection)AUC (horizon error)71.16Unverified
3CNN+FULLAUC (horizon error)58.24Unverified
4DL-IGPAUC (horizon error)57.31Unverified
5VAUC (horizon error)54.43Unverified
#ModelMetricClaimedVerifiedStatus
1VAUC (horizon error)91.1Unverified
2CNN+FULLAUC (horizon error)90.8Unverified
3DL-IGPAUC (horizon error)86.26Unverified
4GoogleNet (Huber Loss, horizon line projection)AUC (horizon error)83.6Unverified
#ModelMetricClaimedVerifiedStatus
1VAUC (horizon error)95.35Unverified
2CNN+FULLAUC (horizon error)94.78Unverified
3DL-IGPAUC (horizon error)94.27Unverified
4GoogleNet (Huber Loss, horizon line projection)AUC (horizon error)86.41Unverified
#ModelMetricClaimedVerifiedStatus
1ConvLSTM (Huber Loss, naive residual path)ATV4.98Unverified