Jul 7, 2023 · In this paper, we propose a novel deep cross-modal hashing method, called Semantic Disentanglement Adversarial Hashing (SDAH), to tackle these challenges for ...
In this paper, we propose a novel deep cross-modal hashing method, called Semantic Disentanglement. Adversarial Hashing (SDAH), to tackle these challenges for.
Specifically, SDAH is designed to decouple the original features of each modality into modality-common features with semantic information and modality-private ...
Aug 4, 2020 · We disentangle sentence query into a semantics graph and capture the local contexts inside the graph via a trilinear model as query clues.
Missing: Disentanglement | Show results with:Disentanglement
A self-supervised adversarial hashing (SSAH) approach, which lies among the early attempts to incorporate adversarial learning into cross-modal hashing in a ...
Mar 18, 2024 · Specifically, this paper designs a novel Semantics Disentangling approach for Cross-Modal Retrieval (termed as SDCMR) to explicitly decouple the ...
This library is an open-source repository that contains cross-modal retrieval methods and codes. 2. Supported Methods
It consists of three major components: (1) a feature learning module that uses CNN or MLP to extract high level semantic representations for the multi-modal ...
Semantic Disentanglement Adversarial Hashing for Cross-Modal Retrieval · Hybrid-attention based Feature-reconstructive Adversarial Hashing Networks for Cross- ...
This paper introduces the Text-Enhanced Graph Attention Hashing for Cross-Modal Retrieval (TEGAH) framework.