Nov 7, 2022 · We pioneer to propose a multi-level fusion model to effectively combine knowledge encoded in multi-modal semantic embeddings together.

In this paper, we propose a multi-level fusion zero shot learning (MLF-ZSL) model to effectively fuse semantic embeddings from multiple modalities.

Abstract:Zero shot learning aims to recognize objects whose instances may not be covered by the training data. To generalize knowledge from seen classes to ...

Dec 10, 2024 · To address the challenges, we propose a Region-Wise Multi-View Representation Learning (ROMER) to capture multi-view dependencies and learn ...

Oct 21, 2022 · A novel Multi-Modal Feature Fusion algorithm (MFF) is proposed to alleviate the domain shift problem of Zero-Shot Learning (ZSL).

We propose a practical Adaptive Multi-scale Semantic Fusion (AMSF) framework to perform object-based multi-scale attribute attention for semantic disambiguation ...

A Vision Transformer-based GZSL method named Depth-Aware Multi-Modal ViT (DAM2ViT), which exploits multi-level features of ViT and incorporates a ...

In this paper, we propose a simple and novel unsupervised method for cross-language entity alignment. We utilize the deep learning multi-language encoder ...

Oct 28, 2024 · The first is how to choose the best independent modalities.The second is how are a set of modalities optimally fused to map to the high-level ...

In this paper, we propose a novel multi-level alignment framework, which hierarchically learns the semantic correlation between multiple levels.