Papers with video representation

2 papers
Modality Alignment between Deep Representations for Effective Video-and-Language Learning (2022.lrec-1)

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Challenge: Existing Video-and-Language models do not take into account the different characteristics of video and text representations.
Approach: They propose a method that exploits Centered Kernel Alignment (CKA) to enhance cross-modality attention by combining multiple modalities.
Outcome: The proposed method outperforms conventional multi-modal methods significantly on video QA tasks with +3.57% accuracy increment compared to the baseline in a popular benchmark dataset.
Dense Procedure Captioning in Narrated Instructional Videos (P19-1)

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Challenge: Existing models for video dense captioning learn video segments and generate captions without considering transcripts.
Approach: They propose a model to generate procedure captions from narrated instructional videos . they extract procedures by a cross-modality module and generate captions by encoding video frames and transcripts within each extracted procedure.
Outcome: The proposed model can extract procedures from narrated instructional videos and generate procedure captions by encoding video frames and transcripts.

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