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Cross-Modal Information Retrieval

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Cross-Modal Information Retrieval (CMIR) is the task of finding relevant items across different modalities. For example, given an image, find a text or vice versa. The main challenge in CMIR is known as the heterogeneity gap: since items from different modalities have different data types, the similarity between them cannot be measured directly. Therefore, the majority of CMIR methods published to date attempt to bridge this gap by learning a latent representation space, where the similarity between items from different modalities can be measured.

Source: Scene-centric vs. Object-centric Image-Text Cross-modal Retrieval: A Reproducibility Study

논문

이 태스크와 하위 분야의 관련 논문입니다. 실제 성능 비교는 평가 결과에서 확인하세요.

Improving Visual-Semantic Embeddings by Learning Semantically-Enhanced Hard Negatives for Cross-modal Information Retrieval

LILE: Look In-Depth before Looking Elsewhere -- A Dual Attention Network using Transformers for Cross-Modal Information Retrieval in Histopathology Archives

Cross-Modal Information Retrieval

논문

Multimodal Representation Alignment for Cross-modal Information Retrieval

jina-clip-v2: Multilingual Multimodal Embeddings for Text and Images

Is Cross-modal Information Retrieval Possible without Training?

Multi-modal Machine Learning in Engineering Design: A Review and Future Directions

VITR: Augmenting Vision Transformers with Relation-Focused Learning for Cross-Modal Information Retrieval

Improving Visual-Semantic Embeddings by Learning Semantically-Enhanced Hard Negatives for Cross-modal Information Retrieval

LILE: Look In-Depth before Looking Elsewhere -- A Dual Attention Network using Transformers for Cross-Modal Information Retrieval in Histopathology Archives

VisualSparta: An Embarrassingly Simple Approach to Large-scale Text-to-Image Search with Weighted Bag-of-words

Learning the Best Pooling Strategy for Visual Semantic Embedding

Fine-grained Visual Textual Alignment for Cross-Modal Retrieval using Transformer Encoders

ZSCRGAN: A GAN-based Expectation Maximization Model for Zero-Shot Retrieval of Images from Textual Descriptions

Cross-modal representation alignment of molecular structure and perturbation-induced transcriptional profiles

CMIR-NET : A Deep Learning Based Model For Cross-Modal Retrieval In Remote Sensing

Scene Graph Reasoning with Prior Visual Relationship for Visual Question Answering

Modeling Text with Graph Convolutional Network for Cross-Modal Information Retrieval

Picture It In Your Mind: Generating High Level Visual Representations From Textual Descriptions