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Rethinking the Bottom-Up Framework for Query-Based Video Localization
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Measured effects reported in the paper
| What was changed | Where | Measured | Effect |
|---|---|---|---|
| GDP vs ABLR-af | bottom-up NLVL · TACoS | mIoU: 13.40 -> 16.18 | Helped |
| GDP vs CGBM | VRL · ActivityNet-VRL | avg mAP@1: 25.7 -> 27.8 | Helped |
| add pyramid hierarchy (ablation) | GDP model A · TACoS | mIoU: 15.3 -> 15.8 | Helped |
| FPN-style adjacent fusion instead of plain pyramid (ablation) | model B · TACoS | mIoU: 15.8 -> 15.7 | No clear effect |
| add Graph-FPN layer (ablation) | model B · TACoS | mIoU: 15.8 -> 16.2 | Helped |
| dense head instead of sparse boundary head (ablation) | GDP · TACoS | mIoU: 12.9 -> 16.2 | Helped |
| dense head instead of sparse boundary head (ablation) | GDP · ActivityNet-VRL | avg mAP@1: 25.2 -> 27.8 | Helped |
| add temporal pooling (ablation) | GDP dense head · TACoS | mIoU: 15.2 -> 16.2 | Helped |
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- Transferable Video Moment Localization by Moment-Guided Query Prompting (AAAI 2024 · similarity 0.88)
- Localizing Events in Videos with Multimodal Queries (CVPR 2025 · similarity 0.87)
- Boundary-Aware Temporal Dynamic Pseudo-Supervision Pairs Generation for Zero-Shot Natural Language Video Localization (AAAI 2025 · similarity 0.87)
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