Sep 15, 2019 · In this paper, we propose a Multimodal Adversarial Network (MAN) method to project the multimodal data into a common space wherein the ...

In this paper, we propose a Multimodal Adversarial Network (MAN) to project the multimodal data into a common space wherein the similarities between different ...

Cross-modal retrieval aims to retrieve the pertinent samples across different modalities, which is important in numerous multimodal applications.

Cross-modal retrieval aims to retrieve the pertinent samples across different modalities, which is important in numerous multimodal applications.

Mar 8, 2023 · The cross-modal molecule retrieval (Text2Mol) task aims to bridge the semantic gap between molecules and natural language descriptions.

In this paper, we present a novel Adversarial Cross-Modal Retrieval (ACMR) method, which seeks an effective common subspace based on adversarial learning.

The MGAN aims to "cluster" matched embeddings of different modalities in the common space by forcing them to be similar to the aggregation. Finally, we train ...

For the modality classifier, the goal is to detect the modality of an item as reliably as possible given an unknown feature projection. For the classifier ...

Cross-modal retrieval aims at retrieving relevant points across different modalities, such as retrieving images via texts. One key challenge of cross-modal ...

The cross-modal molecule retrieval (Text2Mol) task aims to bridge the semantic gap between molecules and natural language descriptions.