Video Event Extraction with Multi-View Interaction Knowledge Distillation Article Swipe
Kaiwen Wei
,
Runyan Du
,
Jin Li
,
Jian Liu
,
Jianhua Yin
,
Linhao Zhang
,
Jin‐Tao Liu
,
Nayu Liu
,
Jingyuan Zhang
,
Zhiyong Guo
·
YOU?
·
· 2024
· Open Access
·
· DOI: https://doi.org/10.1609/aaai.v38i17.29891
YOU?
·
· 2024
· Open Access
·
· DOI: https://doi.org/10.1609/aaai.v38i17.29891
Video event extraction (VEE) aims to extract key events and generate the event arguments for their semantic roles from the video. Despite promising results have been achieved by existing methods, they still lack an elaborate learning strategy to adequately consider: (1) inter-object interaction, which reflects the relation between objects; (2) inter-modality interaction, which aligns the features from text and video modality. In this paper, we propose a Multi-view Interaction with knowledge Distillation (MID) framework to solve the above problems with the Knowledge Distillation (KD) mechanism. Specifically, we propose the self-Relational KD (self-RKD) to enhance the inter-object interaction, where the relation between objects is measured by distance metric, and the high-level relational knowledge from the deeper layer is taken as the guidance for boosting the shallow layer in the video encoder. Meanwhile, to improve the inter-modality interaction, the Layer-to-layer KD (LKD) is proposed, which integrates additional cross-modal supervisions (i.e., the results of cross-attention) with the textual supervising signal for training each transformer decoder layer. Extensive experiments show that without any additional parameters, MID achieves the state-of-the-art performance compared to other strong methods in VEE.
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Metadata
- Type
- article
- Language
- en
- Landing Page
- https://doi.org/10.1609/aaai.v38i17.29891
- https://ojs.aaai.org/index.php/AAAI/article/download/29891/31556
- OA Status
- diamond
- Cited By
- 4
- References
- 67
- Related Works
- 10
- OpenAlex ID
- https://openalex.org/W4393157479
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Raw OpenAlex JSON
- OpenAlex ID
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https://openalex.org/W4393157479Canonical identifier for this work in OpenAlex
- DOI
-
https://doi.org/10.1609/aaai.v38i17.29891Digital Object Identifier
- Title
-
Video Event Extraction with Multi-View Interaction Knowledge DistillationWork title
- Type
-
articleOpenAlex work type
- Language
-
enPrimary language
- Publication year
-
2024Year of publication
- Publication date
-
2024-03-24Full publication date if available
- Authors
-
Kaiwen Wei, Runyan Du, Jin Li, Jian Liu, Jianhua Yin, Linhao Zhang, Jin‐Tao Liu, Nayu Liu, Jingyuan Zhang, Zhiyong GuoList of authors in order
- Landing page
-
https://doi.org/10.1609/aaai.v38i17.29891Publisher landing page
- PDF URL
-
https://ojs.aaai.org/index.php/AAAI/article/download/29891/31556Direct link to full text PDF
- Open access
-
YesWhether a free full text is available
- OA status
-
diamondOpen access status per OpenAlex
- OA URL
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https://ojs.aaai.org/index.php/AAAI/article/download/29891/31556Direct OA link when available
- Concepts
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Distillation, Extraction (chemistry), Computer science, Event (particle physics), Artificial intelligence, Chromatography, Chemistry, Physics, Quantum mechanicsTop concepts (fields/topics) attached by OpenAlex
- Cited by
-
4Total citation count in OpenAlex
- Citations by year (recent)
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2025: 1, 2024: 3Per-year citation counts (last 5 years)
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67Number of works referenced by this work
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10Other works algorithmically related by OpenAlex
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