Cross-modal retrieval: a systematic review of methods and future directions
With the exponential surge in diverse multimodal data, traditional unimodal retrieval
methods struggle to meet the needs of users seeking access to data across various …
methods struggle to meet the needs of users seeking access to data across various …
Hit: Hierarchical transformer with momentum contrast for video-text retrieval
Abstract Video-Text Retrieval has been a hot research topic with the growth of multimedia
data on the internet. Transformer for video-text learning has attracted increasing attention …
data on the internet. Transformer for video-text learning has attracted increasing attention …
User cold-start recommendation via inductive heterogeneous graph neural network
Recently, user cold-start recommendations have attracted a lot of attention from industry and
academia. In user cold-start recommendation systems, the user attribute information is often …
academia. In user cold-start recommendation systems, the user attribute information is often …
Integrating multi-label contrastive learning with dual adversarial graph neural networks for cross-modal retrieval
With the growing amount of multimodal data, cross-modal retrieval has attracted more and
more attention and become a hot research topic. To date, most of the existing techniques …
more attention and become a hot research topic. To date, most of the existing techniques …
Variational causal inference network for explanatory visual question answering
Abstract Explanatory Visual Question Answering (EVQA) is a recently proposed multimodal
reasoning task that requires answering visual questions and generating multimodal …
reasoning task that requires answering visual questions and generating multimodal …
The State of the Art for Cross-Modal Retrieval: A Survey
Cross-modal retrieval, which aims to search for semantically relevant data across different
modalities, has received increasing attention in recent years. Deep learning, with its ability to …
modalities, has received increasing attention in recent years. Deep learning, with its ability to …
Heterogeneous graph contrastive learning network for personalized micro-video recommendation
Personalized micro-video recommendation has attracted a lot of research attention with the
growing popularity of micro-video sharing platforms. Many efforts have been made to …
growing popularity of micro-video sharing platforms. Many efforts have been made to …
Self-supervised correlation learning for cross-modal retrieval
Cross-modal retrieval aims to retrieve relevant data from another modality when given a
query of one modality. Although most existing methods that rely on the label information of …
query of one modality. Although most existing methods that rely on the label information of …
RONO: robust discriminative learning with noisy labels for 2D-3D cross-modal retrieval
Recently, with the advent of Metaverse and AI Generated Content, cross-modal retrieval
becomes popular with a burst of 2D and 3D data. However, this problem is challenging …
becomes popular with a burst of 2D and 3D data. However, this problem is challenging …
LDRE: LLM-based Divergent Reasoning and Ensemble for Zero-Shot Composed Image Retrieval
Zero-Shot Composed Image Retrieval (ZS-CIR) has garnered increasing interest in recent
years, which aims to retrieve a target image based on a query composed of a reference …
years, which aims to retrieve a target image based on a query composed of a reference …