Learning Selective Self-Mutual Attention for RGB-D Saliency Detection

CVPR 2020 Nian Liu Ni Zhang Junwei Han

Saliency detection on RGB-D images is receiving more and more research interests recently. Previous models adopt the early fusion or the result fusion scheme to fuse the input RGB and depth data or their saliency maps, which incur the problem of distribution gap or information loss... (read more)

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Results from the Paper


TASK DATASET MODEL METRIC NAME METRIC VALUE GLOBAL RANK BENCHMARK
RGB-D Salient Object Detection NJU2K S2MA S-Measure 89.4 # 10
Average MAE 0.053 # 12
max E-Measure 92.7 # 5
max F-Measure 88.9 # 7

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