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Local Background Enclosure for RGB-D Salient Object Detection

1 Jun 2016CVPR 2016 6archive 2025-07-28

David Feng, Nick Barnes, ShaoDi You, Chris McCarthy

Recent work in salient object detection has considered the incorporation of depth cues from RGB-D images. In most cases, depth contrast is used as the main feature. However, areas of high contrast in background regions cause false positives for such methods, as the background frequently contains regions that are highly variable in depth. Here, we propose a novel RGB-D saliency feature. Local Background Enclosure (LBE) captures the spread of angular directions which are background with respect to the candidate region and the object that it is part of. We show that our feature improves over state-of-the-art RGB-D saliency approaches as well as RGB methods on the RGBD1000 and NJUDS2000 datasets.

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Tasks

ObjectObject DetectionRGB Salient Object DetectionRGB-D Salient Object DetectionSalient Object Detectionobject-detection

Results from the paper archive 2025-07-28

TaskDatasetModelMetricValueRank at snapshotLeaderboardReport
RGB-D Salient Object Detection NJU2K LBE Average MAE 0.153 #25 of 27 Archive leaderboard report
RGB-D Salient Object Detection NJU2K LBE S-Measure 69.5 #25 of 27 Archive leaderboard report
RGB-D Salient Object Detection NJU2K LBE max E-Measure 80.3 #25 of 27 Archive leaderboard report
RGB-D Salient Object Detection NJU2K LBE max F-Measure 74.8 #25 of 27 Archive leaderboard report

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