mlsanityData to 14 Oct 2026

Exploiting Context Information for Generic Event Boundary Captioning

arXiv 2207.01050 ↗First posted 3 Jul 2022cs.CVcited by 3

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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

  1. 2017Attention Is All You Needcited by 60,361
  2. 2021Learning Transferable Visual Models From Natural Language Supervisioncited by 33,744
  3. 2020Deformable DETR: Deformable Transformers for End-to-End Object Detectioncited by 3,422
  4. 2022Omnivore: A Single Model for Many Visual Modalitiescited by 215
  5. 2021End-to-End Dense Video Captioning with Parallel Decodingcited by 133

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Citing papers per year: 2023: 1; 2024: 2.

3 papers.