We propose a new cross-modal correlation learning framework which boosts the performance of correlation learning models using the hyperlink information.
ABSTRACT. We propose a new cross-modal correlation learning frame- work which boosts the performance of correlation learning models using the hyperlink ...
We propose a new cross-modal correlation learning framework which boosts the performance of correlation learning models using the hyperlink information.
Apr 30, 2024 · This paper aims to explicitly learn potential cross-modal correlation to enhance deepfake detection towards various generation scenarios.
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Apr 27, 2021 · In this work, we propose a framework called “Improvement of Deep Cross-Modal Retrieval (IDCMR)”, which generates real-valued representation.
Aug 1, 2024 · This paper explores a new way to take advantage of cross-modal guidance without gold labels on coherency, and proposes the Weak Cross-Modal Guided Ordering ( ...
In this paper, we propose the Context-guided Cross-modal Correlation Learning (CCCL) framework for ITR under a novel paradigm: “Perceive, Reason, and Align”.
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Another approach is to automatically discover hidden links between visual and textual elements using unsupervised learning methods (Clinchant et al.
Apr 27, 2024 · It aims to comprehend and link diverse data, providing comprehensive insights by merging different modes. Cross-modal retrieval, a specialized ...
In this paper, we concentrated on harmonizing cross-modal representation learning and the full-cycle modeling of high-level semantic associations between ...