Multimodal Embeddings
Related Papers
Learning Abstract Concept Embeddings from Multi-Modal Data: Since You Probably Can’t See What I Mean
Concept Embeddings from Multi-Modal Data: Since You Probably Can’t See What I Mean Felix Hill Computer Laboratory University of Cambridge felix.hill@cl.cam.ac.uk Anna Korhonen Computer Laboratory University of Cambridge anna.korhonen@cl.cam.ac.uk Abstract …...
Divide, Conquer and Combine: Hierarchical Feature Fusion Network with Local and Global Perspectives for Multimodal Affective Computing
AbstractWe propose a general strategy named ‘divide, conquer and combine’ for multimodal fusion. Instead of directly fusing features at holistic level, we conduct fusion hierarchically so that both local and …...
NUAA-QMUL at SemEval-2020 Task 8: Utilizing BERT and DenseNet for Internet Meme Emotion Analysis
AbstractThis paper describes our contribution to SemEval 2020 Task 8: Memotion Analysis. Our system learns multi-modal embeddings from text and images in order to classify Internet memes by sentiment. Our …...
Leverage Points in Modality Shifts: Comparing Language-only and Multimodal Word Representations
AbstractMultimodal embeddings aim to enrich the semantic information in neural representations of language compared to text-only models. While different embeddings exhibit different applicability and performance on downstream tasks, little is …...
OPI at SemEval-2023 Task 1: Image-Text Embeddings and Multimodal Information Retrieval for Visual Word Sense Disambiguation
AbstractThe goal of visual word sense disambiguation is to find the image that best matches the provided description of the word’s meaning. It is a challenging problem, requiring approaches that …...