Non-Local Deep Features for Salient Object Detection

Saliency detection aims to highlight the most relevant objects in an image. Methods using conventional models struggle whenever salient objects are pictured on top of a cluttered background while deep neural nets suffer from excess complexity and slow evaluation speeds... (read more)

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Results from the Paper


TASK DATASET MODEL METRIC NAME METRIC VALUE GLOBAL RANK BENCHMARK
RGB Salient Object Detection SOC NLDF S-Measure 0.816 # 5
mean E-Measure 0.837 # 5
Average MAE 0.106 # 5

Results from Other Papers


TASK DATASET MODEL METRIC NAME METRIC VALUE GLOBAL RANK SOURCE PAPER COMPARE
RGB Salient Object Detection DUTS-TE NLDF MAE 0.065 # 10
F-measure 0.816 # 7
RGB Salient Object Detection ISTD NLDF Balanced Error Rate 7.50 # 4
RGB Salient Object Detection SBU NLDF Balanced Error Rate 7.02 # 5
RGB Salient Object Detection UCF NLDF Balanced Error Rate 7.69 # 2

Methods used in the Paper


METHOD TYPE
🤖 No Methods Found Help the community by adding them if they're not listed; e.g. Deep Residual Learning for Image Recognition uses ResNet