Exploiting Context Information for Generic Event Boundary Captioning
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Abstract (arXiv)
Generic Event Boundary Captioning (GEBC) aims to generate three sentences describing the status change for a given time boundary. Previous methods only process the information of a single boundary at a time, which lacks utilization of video context information. To tackle this issue, we design a model that directly takes the whole video as input and generates captions for all boundaries parallelly. The model could learn the context information for each time boundary by modeling the boundary-boundary interactions. Experiments demonstrate the effectiveness of context information. The proposed method achieved a 72.84 score on the test set, and we reached the 2nd place in this challenge. Our code is available at: urlhttps://github.com/zjr2000/Context-GEBC
Key facts. Cited by 3 papers in the map (data through 14 Oct 2026). Builds on 5 of its 9 references that are in the map. First posted on arXiv 3 Jul 2022.
Builds on
5 of 9 references.
References · 5
- 2017Attention Is All You Needcited by 60,361
- 2021Learning Transferable Visual Models From Natural Language Supervisioncited by 33,744
- 2020Deformable DETR: Deformable Transformers for End-to-End Object Detectioncited by 3,422
- 2022Omnivore: A Single Model for Many Visual Modalitiescited by 215
- 2021End-to-End Dense Video Captioning with Parallel Decodingcited by 133
Built on by
Citing papers per year: 2023: 1; 2024: 2.
3 papers.
- 2024V2Xum-LLM: Cross-Modal Video Summarization with Temporal Prompt Instruction Tuning18 Apr 2024
- 2024Empowering LLMs with Pseudo-Untrimmed Videos for Audio-Visual Temporal Understanding24 Mar 2024
- 2023LLMVA-GEBC: Large Language Model with Video Adapter for Generic Event Boundary Captioning17 Jun 2023