In this work, we study the unsupervised video object segmentation problem where moving objects are segmented without prior knowledge of these objects. First, we propose a motion-based bilateral network to estimate the background based on the motion pattern of non-object regions... (read more)
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Ranked #2 on
Video Object Segmentation
on DAVIS 2016
(Average MAE metric)
TASK | DATASET | MODEL | METRIC NAME | METRIC VALUE | GLOBAL RANK | USES EXTRA TRAINING DATA |
BENCHMARK |
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Video Object Segmentation | DAVIS 2016 | MBNM | Average MAE | 0.031 | # 2 |
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Video Salient Object Detection | DAVIS-2016 | MBNM | S-Measure | 0.887 | # 2 |
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MAX E-MEASURE | 0.966 | # 1 |
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MAX F-MEASURE | 0.862 | # 1 |
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AVERAGE MAE | 0.031 | # 6 |
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Video Salient Object Detection | DAVSOD-easy35 | MBNM | S-Measure | 0.646 | # 4 |
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max F-Measure | 0.506 | # 4 |
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max E-Measure | 0.694 | # 4 |
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Average MAE | 0.109 | # 3 |
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Video Salient Object Detection | DAVSOD-Normal25 | MBNM | S-Measure | 0.597 | # 4 |
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max E-measure | 0.665 | # 4 |
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Average MAE | 0.127 | # 3 |
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Video Salient Object Detection | FBMS-59 | MBNM | S-Measure | 0.857 | # 3 |
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AVERAGE MAE | 0.047 | # 2 |
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MAX E-MEASURE | 0.892 | # 2 |
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MAX F-MEASURE | 0.816 | # 4 |
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Video Salient Object Detection | MCL | MBNM | S-Measure | 0.755 | # 3 |
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MAX E-MEASURE | 0.858 | # 3 |
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MAX F-MEASURE | 0.698 | # 2 |
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AVERAGE MAE | 0.119 | # 3 |
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Video Salient Object Detection | SegTrack v2 | MBNM | S-Measure | 0.809 | # 3 |
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MAX F-MEASURE | 0.716 | # 2 |
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AVERAGE MAE | 0.026 | # 5 |
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max E-measure | 0.878 | # 3 |
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Video Salient Object Detection | UVSD | MBNM | S-Measure | 0.698 | # 4 |
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max E-measure | 0.776 | # 4 |
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Average MAE | 0.079 | # 4 |
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Video Salient Object Detection | ViSal | MBNM | S-Measure | 0.857 | # 4 |
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max E-measure | 0.892 | # 3 |
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Average MAE | 0.047 | # 4 |
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Video Salient Object Detection | VOS-T | MBNM | S-Measure | 0.742 | # 4 |
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max E-measure | 0.797 | # 4 |
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Average MAE | 0.099 | # 5 |
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METHOD | TYPE | |
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🤖 No Methods Found | Help the community by adding them if they're not listed; e.g. Deep Residual Learning for Image Recognition uses ResNet |