Oct 27, 2023 · In this paper, we introduce a novel SemVTR framework designed to learn semantics-grounded video-text representations in a vocabulary space.
Learning Semantics-Grounded Vocabulary Representation for ...
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Enhancing the ability to associate finegrained video-text information is an effective way to improve the performance of dual-encoder models. ...
A novel SemVTR framework designed to learn semantics-grounded video- text representations in a vocabulary space, in which each dimension corresponds to a ...
Feb 26, 2024 · A two-stage semantics grounding approach is proposed to activate semantically relevant dimensions and suppress irrelevant dimensions. The ...
Learning semantics-grounded vocabulary representation for video-text retrieval. Y Shi, H Liu, H Xu, Z Ma, Q Ye, A Hu, M Yan, J Zhang, F Huang, C Yuan ...
May 20, 2024 · Keywords: video-text retrieval, lexicon representation, unified learning ... For lexicon representation learning, we propose a two-stage semantics ...
The current study aims to leverage visual information in order to capture sentence level semantics without the need for word embeddings. We use a multimodal ...
May 20, 2024 · In this paper we propose a novel strategy for the selection of both positive and negative pairs which takes into account both the annotations and the semantic ...
Missing: Grounded Vocabulary
Video Paragraph Grounding (VPG) is an essential yet challenging task in vision-language understanding, which aims to jointly localize multiple events from ...
Missing: Vocabulary | Show results with:Vocabulary
Abstract—There is growing interest in models that can learn from unlabelled speech paired with visual context. This setting is.