Research map / Video / Video-language understanding
Open-Book Video Captioning With Retrieve-Copy-Generate Network
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Measured effects reported in the paper
| What was changed | Where | Measured | Effect |
|---|---|---|---|
| Add retrieved sentence guidance through a fixed retriever | Hierarchical-LSTM captioning on MSR-VTT · MSR-VTT test | CIDEr: 49.8 -> 52.3 | Helped |
| Add retrieved sentence guidance with joint retriever training | Hierarchical-LSTM captioning on VATEX · VATEX test | CIDEr: 49.2 -> 57.5 | Helped |
| Add ResNet appearance and I3D motion features to the retriever (ablation) | RCG with a fixed VATEX retriever · VATEX test | CIDEr: 49.2 -> 56.8 | Helped |
| Replace the random retriever with a ResNet-only retriever (ablation) | RCG with a fixed VATEX retriever · VATEX test | CIDEr: 49.1 -> 51.5 | Helped |
| Replace the random retriever with an I3D-only retriever (ablation) | RCG with a fixed VATEX retriever · VATEX test | CIDEr: 49.1 -> 54.7 | Helped |
| Jointly train the retriever instead of keeping it fixed, using 3 retrievals during training (ablation) | RCG on VATEX · VATEX test | CIDEr: 56.8 -> 57.5 | Helped |
| Train with 3 retrieved sentences instead of 1, with a fixed retriever (ablation) | RCG on VATEX · VATEX test | CIDEr: 55.3 -> 56.8 | Helped |
| Train with 5 or 10 retrieved sentences instead of 3, with a fixed retriever (ablation) | RCG on VATEX · VATEX test | CIDEr: 56.8 -> 56.3; 56.8 -> 56.4 | Hurt |
| Increase the number of retrieved sentences at inference from 1 to 30 (ablation) | RCG trained with 3 retrieved sentences · VATEX test | CIDEr: 50.5 -> 57.5 | Helped |
| Expand the retrieval corpus from +0.1% to +100% (ablation) | RCG on VATEX · VATEX test | CIDEr: 39.9 -> 56.8 | Helped |
| Use an Oracle retrieval corpus containing test-set sentences (ablation) | RCG on VATEX · VATEX test | CIDEr: 56.8 -> 58.9 | Helped |
Closest papers by meaning
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- VideoCon: Robust Video-Language Alignment via Contrast Captions (CVPR 2024 · similarity 0.86)
- Panda-70M: Captioning 70M Videos with Multiple Cross-Modality Teachers (CVPR 2024 · similarity 0.85)
- OmniViD: A Generative Framework for Universal Video Understanding (CVPR 2024 · similarity 0.85)
- Fine-Grained Captioning of Long Videos through Scene Graph Consolidation (ICML 2025 · similarity 0.85)
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