Research map / Video / Video-language understanding
Dense Regression Network for Video Grounding
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Measured effects reported in the paper
| What was changed | Where | Measured | Effect |
|---|---|---|---|
| Use dense regression from all frames within the ground truth instead of sparse subsets (ablation) | DRN · Charades-STA | R@1, IoU=0.5: 38.36 -> 45.40 | Helped |
| Use dense regression from all frames within the ground truth instead of sparse subsets (ablation) | DRN · Charades-STA | R@5, IoU=0.5: 83.36 -> 88.01 | Helped |
| Add an IoU regression head to score localization quality (ablation) | DRN · Charades-STA | R@1, IoU=0.5: 44.13 -> 45.40 | Helped |
| Replace the IoU regression head with a centerness head (ablation) | DRN · Charades-STA | R@1, IoU=0.5: 45.40 -> 44.02 | Hurt |
| Add an IoU regression head to score localization quality (ablation) | DRN · ActivityNet-Captions | R@1, IoU=0.5: 40.44 -> 42.49 | Helped |
| Replace the IoU regression head with a centerness head (ablation) | DRN · ActivityNet-Captions | R@1, IoU=0.5: 42.49 -> 39.83 | Hurt |
| Add multi-level fusion (ablation) | DRN · Charades-STA | R@1, IoU=0.5: 43.04 -> 43.79 | Helped |
| Add temporal location embedding (ablation) | DRN · Charades-STA | R@1, IoU=0.5: 43.04 -> 43.47 | Helped |
| Add multi-level fusion and temporal location embedding together (ablation) | DRN · Charades-STA | R@1, IoU=0.5: 43.04 -> 45.40 | Helped |
| Add multi-level fusion (ablation) | DRN · ActivityNet-Captions | R@1, IoU=0.5: 39.78 -> 40.61 | Helped |
| Add temporal location embedding (ablation) | DRN · ActivityNet-Captions | R@1, IoU=0.5: 39.78 -> 40.96 | Helped |
| Use distinct query features at different fusion levels rather than the same query feature (ablation) | DRN · Charades-STA | R@1, IoU=0.5: 44.76 -> 45.40 | Helped |
Closest papers by meaning
- VideoGrounding-DINO: Towards Open-Vocabulary Spatio-Temporal Video Grounding (CVPR 2024 · similarity 0.88)
- Comprehensive Visual Grounding for Video Description (AAAI 2024 · similarity 0.87)
- Temporal Sentence Grounding with Relevance Feedback in Videos (NeurIPS 2024 · similarity 0.86)
- VideoGEM: Training-free Action Grounding in Videos (CVPR 2025 · similarity 0.86)
- SnAG: Scalable and Accurate Video Grounding (CVPR 2024 · similarity 0.86)
- DeCafNet: Delegate and Conquer for Efficient Temporal Grounding in Long Videos (CVPR 2025 · similarity 0.86)
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