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+We invite submissions presenting new and original research on topics including but not limited to the following:
+
+   - Cross-Modal Learning and Representation
+   - Multi-Modal Object Detection and Tracking
+   - Multi-Modal Video Understanding
+   - Multi-Modal Machine Learning in Healthcare
+   - Few-Shot and Zero-Shot Learning in Multi-Modal Systems
+   - Applications of Multi-Modal Learning in Social Media
+
+## Paper Submission and Review
+ICPR-2024 will follow a single-blind review process. Authors can include their names and affiliations in the manuscript. Also, the authors can submit their arXiv papers in ICPR-2024.
+## Paper Format and Length
+Springer LNCS format with maximum 15 pages (including references) during paper submission. There is no minimum page limit. To take care of reviewers' comments, one more page is allowed (without any charge) during revised/camera ready submission. Moreover, authors may purchase up to 2 extra pages. Extra page charges must be paid at the time of registration.
+
+Springer LNCS paper formatting instructions and templates for ICPR-2024 are available here [DOC](https://icpr2024.org/pdf/ICPR_2024_DOC_Templates.zip) and [LaTeX](https://icpr2024.org/pdf/ICPR_2024_LaTeX_Templates.zip).
+## Supplementary materials
+By the submission deadline, the authors may optionally submit additional material that was ready at the time of paper submission but could not be included due to constraints of format or space. The authors should refer to the contents of the supplementary material appropriately in the paper. Reviewers will be encouraged to look at it, but are not obligated to do so.
+
+Supplementary material may include videos, proofs, additional figures or tables, more detailed analysis of experiments presented in the paper. There is no page limit for the supplementary materials but only one file with maximum file size of 50 MB is allowed for submission.
+
+We encourage (if possible) authors to upload their code as part of their supplementary material in order to help reviewers assess the quality of the work.