Video-Text Prompting for Weakly Supervised Spatio-Temporal Video Grounding (2024.emnlp-main)
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| Challenge: | Existing methods extract each candidate tube feature independently by cropping objects from video frame feature, discarding all contextual information such as position change and inter-entity relationship. |
| Approach: | They propose to use video-text prompts to construct candidate feature instead of cropping tube region from feature map . they also propose negative contrastive samples whose candidate object is erased instead of being highlighted . |
| Outcome: | The proposed methods surpass existing weakly-supervised methods by a great margin . they draw visual markers over objects tubes as video prompts . |
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