Shifting More Attention to Video Salient Object Detection

The last decade has witnessed a growing interest in video salient object detection (VSOD). However, the research community long-term lacked a well-established VSOD dataset representative of real dynamic scenes with high-quality annotations... To address this issue, we elaborately collected a visual-attention-consistent Densely Annotated VSOD (DAVSOD) dataset, which contains 226 videos with 23,938 frames that cover diverse realistic-scenes, objects, instances and motions. With corresponding real human eye-fixation data, we obtain precise ground-truths. This is the first work that explicitly emphasizes the challenge of saliency shift, i.e., the video salient object(s) may dynamically change. To further contribute the community a complete benchmark, we systematically assess 17 representative VSOD algorithms over seven existing VSOD datasets and our DAVSOD with totally 84K frames (largest-scale). Utilizing three famous metrics, we then present a comprehensive and insightful performance analysis. Furthermore, we propose a baseline model. It is equipped with a saliency shift- aware convLSTM, which can efficiently capture video saliency dynamics through learning human attention-shift behavior. Extensive experiments open up promising future directions for model development and comparison. read more

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Task Dataset Model Metric Name Metric Value Global Rank Uses Extra
Training Data
Benchmark
Video Object Segmentation DAVIS 2016 SSAV S-Measure 0.893 # 1
Average MAE 0.028 # 1
max E-Measure .948 # 1
max F-Measure 0.861 # 1
Video Salient Object Detection DAVIS-2016 SSAV S-Measure 0.893 # 1
MAX E-MEASURE 0.948 # 3
MAX F-MEASURE 0.861 # 2
AVERAGE MAE 0.028 # 7
Video Salient Object Detection DAVSOD-Difficult20 SSAV S-Measure 0.619 # 1
max E-measure 0.696 # 3
Average MAE 0.114 # 2
Video Salient Object Detection DAVSOD-easy35 SSAV S-Measure 0.755 # 1
max F-Measure 0.659 # 1
max E-Measure 0.806 # 1
Average MAE 0.084 # 1
Video Salient Object Detection DAVSOD-Normal25 SSAV S-Measure 0.661 # 1
max E-measure 0.723 # 1
Average MAE 0.117 # 1
Video Salient Object Detection FBMS-59 SSAV S-Measure 0.879 # 1
AVERAGE MAE 0.040 # 1
MAX E-MEASURE 0.926 # 1
MAX F-MEASURE 0.865 # 1
Video Salient Object Detection MCL SSAV S-Measure 0.819 # 2
MAX E-MEASURE 0.889 # 2
MAX F-MEASURE 0.773 # 1
AVERAGE MAE 0.026 # 7
Video Salient Object Detection SegTrack v2 SSAV S-Measure 0.850 # 2
MAX F-MEASURE 0.801 # 1
AVERAGE MAE 0.023 # 1
max E-measure 0.917 # 2
Video Salient Object Detection UVSD SSAV S-Measure 0.860 # 2
max E-measure 0.939 # 2
Average MAE 0.025 # 2
Video Salient Object Detection ViSal SSAV S-Measure 0.942 # 1
max E-measure 0.980 # 1
Average MAE 0.021 # 1
Video Salient Object Detection VOS-T SSAV S-Measure 0.819 # 2
max E-measure 0.839 # 2
Average MAE 0.074 # 2

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