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Found 3 papers, 2 papers with code
Can representation learning for multimodal image registration be improved by supervision of intermediate layers?
Contrastive learning can generate representations of multimodal images, reducing the challenging task of multimodal image registration to a monomodal one.
Cross-Modality Sub-Image Retrieval using Contrastive Multimodal Image Representations
We propose a new application-independent content-based image retrieval (CBIR) system for reverse (sub-)image search across modalities, which combines deep learning to generate representations (embedding the different modalities in a common space) with classical feature extraction and bag-of-words models for efficient and reliable retrieval.
CoMIR: Contrastive Multimodal Image Representation for Registration
We propose contrastive coding to learn shared, dense image representations, referred to as CoMIRs (Contrastive Multimodal Image Representations).
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