Pub Date : 2024-07-11DOI: 10.1109/mmul.2024.3414104
{"title":"IEEE Computer Society Has You Covered!","authors":"","doi":"10.1109/mmul.2024.3414104","DOIUrl":"https://doi.org/10.1109/mmul.2024.3414104","url":null,"abstract":"","PeriodicalId":13240,"journal":{"name":"IEEE MultiMedia","volume":"40 1","pages":""},"PeriodicalIF":3.2,"publicationDate":"2024-07-11","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"141610230","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":4,"RegionCategory":"计算机科学","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}
Pub Date : 2024-07-11DOI: 10.1109/mmul.2024.3413395
Minhas Kamal, Balakrishnan Prabhakaran
Generative AI refers to algorithms and techniques designed to generate text, images, videos, or other data, typically in response to prompts. These algorithms leverage large generative models that learn the patterns and structures of the media data (text, images, or videos) provided during training and then generate new media data that have analogous characteristics. Much of the recent research has gone into applying generative AI for text and 2-D image data. However, generative AI for 3-D models, especially 3-D point cloud data (PCD), has compelling applications in virtual reality content generation, gaming, and product design and manufacturing, but it introduces a multitude of research challenges.
{"title":"Generative AI for 3-D Point Clouds","authors":"Minhas Kamal, Balakrishnan Prabhakaran","doi":"10.1109/mmul.2024.3413395","DOIUrl":"https://doi.org/10.1109/mmul.2024.3413395","url":null,"abstract":"Generative AI refers to algorithms and techniques designed to generate text, images, videos, or other data, typically in response to prompts. These algorithms leverage large generative models that learn the patterns and structures of the media data (text, images, or videos) provided during training and then generate new media data that have analogous characteristics. Much of the recent research has gone into applying generative AI for text and 2-D image data. However, generative AI for 3-D models, especially 3-D point cloud data (PCD), has compelling applications in virtual reality content generation, gaming, and product design and manufacturing, but it introduces a multitude of research challenges.","PeriodicalId":13240,"journal":{"name":"IEEE MultiMedia","volume":"25 1","pages":""},"PeriodicalIF":3.2,"publicationDate":"2024-07-11","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"141614566","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":4,"RegionCategory":"计算机科学","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}
Pub Date : 2024-07-09DOI: 10.1109/mmul.2024.3423370
Preetam Amrit, Naman Baranwal, Kedar Nath Singh, Amit Kumar Singh
{"title":"ConvNet-HIDE: Deep Learning-Based Dual Watermarking for Healthcare Images","authors":"Preetam Amrit, Naman Baranwal, Kedar Nath Singh, Amit Kumar Singh","doi":"10.1109/mmul.2024.3423370","DOIUrl":"https://doi.org/10.1109/mmul.2024.3423370","url":null,"abstract":"","PeriodicalId":13240,"journal":{"name":"IEEE MultiMedia","volume":"64 1","pages":""},"PeriodicalIF":3.2,"publicationDate":"2024-07-09","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"141573436","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":4,"RegionCategory":"计算机科学","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}
Pub Date : 2024-07-04DOI: 10.1109/mmul.2024.3421575
Jianhua Zhu, Changjiang Liu, Yang Yang
{"title":"Robust Image Registration for Power Equipment Using Large Gap Fracture Contours","authors":"Jianhua Zhu, Changjiang Liu, Yang Yang","doi":"10.1109/mmul.2024.3421575","DOIUrl":"https://doi.org/10.1109/mmul.2024.3421575","url":null,"abstract":"","PeriodicalId":13240,"journal":{"name":"IEEE MultiMedia","volume":"29 1","pages":""},"PeriodicalIF":3.2,"publicationDate":"2024-07-04","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"141548578","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":4,"RegionCategory":"计算机科学","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}
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