List your company
ResearchFormerly WizWand

Semantic Segmentation on Barcelona (test)

74.6Global AccuracyVGG-conv5-DAG-RNN(8)
45.27252.88660.568.114Sep 2, 2015
Updated 8mo ago

Evaluation results

MethodLinks
VGG-conv5-DAG-RNN(8)Backbone=VGG-conv5, RNN iterations=82015.0974.624.6
VGG-conv5-DAG-RNN(8)Backbone=VGG-conv5, DAG-RNN=true, Iterations=82015.0974.624.6
VGG-conv5-ENNBackbone=VGG-conv5, ENN=true2015.0973.321.1
VGG-conv5-ENNBackbone=VGG-conv5, ENN=true2015.0973.321.1
CNN-65-DAG-RNN(8)Backbone=CNN-65, RNN iterations=82015.0972.414.5
CNN-65-DAG-RNN(8)Backbone=CNN-65, DAG-RNN=true, Iterations=82015.0972.414.5
CNN-65-DAG-RNN(4)Backbone=CNN-65, RNN iterations=42015.0971.312.9
CNN-65-DAG-RNN(4)Backbone=CNN-65, DAG-RNN=true, Iterations=42015.0971.312.9
CNN-65Backbone=CNN-652015.096910.5
CNN-65-ENNBackbone=CNN-65, ENN=true2015.096911
CNN-65Backbone=CNN-652015.096910.5
CNN-65-ENNBackbone=CNN-65, ENN=true2015.096911
Farabet et al.ranking_in_table=second entry2015.0967.89.5
Farabet et al.variant=22015.0967.89.5
Tighe et al.2015.0966.97.6
Tighe et al.2015.0966.97.6
Farabet et al.ranking_in_table=first entry2015.0946.412.5
Farabet et al.variant=12015.0946.412.5