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Found 10 papers, 0 papers with code
Prototype-Enhanced Hypergraph Learning for Heterogeneous Information Networks
The variety and complexity of relations in multimedia data lead to Heterogeneous Information Networks (HINs).
Multimodal Temporal Fusion Transformers Are Good Product Demand Forecasters
Traditional approaches to demand forecasting rely on historical demand, product categories, and additional contextual information such as seasonality and events.
PanorAMS: Automatic Annotation for Detecting Objects in Urban Context
With the PanorAMS framework we introduce a method to automatically generate bounding box annotations for panoramic images based on urban context information.
Adaptive Neural Message Passing for Inductive Learning on Hypergraphs
Most hypergraph learning approaches convert the hypergraph structure to that of a graph and then deploy existing geometric deep learning methods.
Graph Neural Networks for Knowledge Enhanced Visual Representation of Paintings
We propose ArtSAGENet, a novel multimodal architecture that integrates Graph Neural Networks (GNNs) and Convolutional Neural Networks (CNNs), to jointly learn visual and semantic-based artistic representations.
HyperSAGE: Generalizing Inductive Representation Learning on Hypergraphs
To model such complex relations, hypergraphs have proven to be a natural representation.
HyperLearn: A Distributed Approach for Representation Learning in Datasets With Many Modalities
Encoding multimedia items into a continuous low-dimensional semantic space such that both types of relations are captured and preserved is extremely challenging, especially if the goal is a unified end-to-end learning framework.
Interactive Search and Exploration in Online Discussion Forums Using Multimodal Embeddings
In this paper we present a novel interactive multimodal learning system, which facilitates search and exploration in large networks of social multimedia users.
Multimodal Classification of Urban Micro-Events
In this paper we explore several methods of creating such a classifier, including early, late, hybrid fusion and representation learning using multimodal graphs.
Exquisitor: Interactive Learning at Large
Increasing scale is a dominant trend in today's multimedia collections, which especially impacts interactive applications.
