English
 
Help Privacy Policy Disclaimer
  Advanced SearchBrowse

Item

ITEM ACTIONSEXPORT

Released

Conference Paper

Probabilistic Compositional Embeddings for Multimodal Image Retrieval

MPS-Authors
/persons/resource/persons127761

Akata,  Zeynep       
Dept. Empirical Inference, Max Planck Institute for Intelligent Systems, Max Planck Society;
External Organizations;

Fulltext (restricted access)
There are currently no full texts shared for your IP range.
Fulltext (public)
There are no public fulltexts stored in PuRe
Supplementary Material (public)
There is no public supplementary material available
Citation

Neculai, A., Chen, Y., & Akata, Z. (2022). Probabilistic Compositional Embeddings for Multimodal Image Retrieval. In 2022 IEEE/CVF Conference on Computer Vision and Pattern Recognition Workshops (CVPRW 2022) (pp. 4546-4556). Piscataway, NJ: IEEE. doi:10.1109/CVPRW56347.2022.00501.


Cite as: https://hdl.handle.net/21.11116/0000-0010-2F9A-D
Abstract
There is no abstract available