Research map / Video / Video segmentation and tracking
Revisiting Video Saliency: A Large-Scale Benchmark and a New Model
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Measured effects reported in the paper
| What was changed | Where | Measured | Effect |
|---|---|---|---|
| add the supervised attention module and static-image training (ablation) | Ours · DHF1K | AUC-J: 0.847 -> 0.890 | Helped |
| add a residual connection to the attention module (ablation) | Ours · DHF1K | AUC-J: 0.874 -> 0.890 | Helped |
| add downsampling to enlarge the attention module's receptive field (ablation) | Ours · DHF1K | AUC-J: 0.870 -> 0.890 | Helped |
| increase static-image training data from 5K to 10K images (ablation) | Ours · DHF1K | AUC-J: 0.877 -> 0.890 | Helped |
| add convLSTM for temporal modeling (ablation) | Ours · DHF1K | AUC-J: 0.867 -> 0.890 | Helped |
| use the proposed attentive CNN-LSTM instead of the strongest listed baseline | video saliency models · DHF1K test | NSS: 1.911 -> 2.354 | Helped |
| use the proposed attentive CNN-LSTM instead of the strongest listed baseline | video saliency models · Hollywood-2 test | NSS: 2.459 -> 3.086 | Helped |
| use the proposed attentive CNN-LSTM instead of the strongest listed baseline | video saliency models · UCF sports test | NSS: 2.311 -> 3.200 | Helped |
Closest papers by meaning
- Going From Image to Video Saliency: Augmenting Image Salience With Dynamic Attentional Push (CVPR 2018 · similarity 0.93)
- A Motion-aware Spatio-temporal Graph for Video Salient Object Ranking (NeurIPS 2024 · similarity 0.91)
- Shifting More Attention to Video Salient Object Detection (CVPR 2019 · similarity 0.91)
- A Deeper Look at Saliency: Feature Contrast, Semantics, and Beyond (CVPR 2016 · similarity 0.90)
- Recurrent Mixture Density Network for Spatiotemporal Visual Attention (ICLR 2017 · similarity 0.90)
- CaRDiff: Video Salient Object Ranking Chain of Thought Reasoning for Saliency Prediction with Diffusion (AAAI 2025 · similarity 0.90)
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