IEEE MultiMedia最新文献_第7页

Optimizing Multidimensional Perceptual Quality in Online Interactive Multimedia 优化在线交互式多媒体的多维感知质量

IF 3.2 4区计算机科学

IEEE MultiMedia Pub Date : 2023-07-01 DOI: 10.1109/MMUL.2023.3277851

Benjamin W. Wah, Jingxi X. Xu

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引用次数: 0

An Improved Interaction Estimation and Optimization Method for Surveillance Video Synopsis 一种改进的监控视频摘要交互估计与优化方法

IF 3.2 4区计算机科学

IEEE MultiMedia Pub Date : 2023-07-01 DOI: 10.1109/MMUL.2022.3224874

K. Namitha, M. Geetha, N.Rev athi

引用次数: 1

IEEE Computer Society CG&A IEEE计算机学会

4区计算机科学

IEEE MultiMedia Pub Date : 2023-07-01 DOI: 10.1109/mmul.2023.3309016

引用次数: 0

Taking a “Deep” Look at Multimedia Streaming “深入”了解多媒体流媒体

4区计算机科学

IEEE MultiMedia Pub Date : 2023-07-01 DOI: 10.1109/mmul.2023.3308401

Balakrishnan Prabhakaran

引用次数: 0

IEEE Annals of the History of Computing IEEE计算历史年鉴

4区计算机科学

IEEE MultiMedia Pub Date : 2023-07-01 DOI: 10.1109/mmul.2023.3309015

引用次数: 0

Reversible Modal Conversion Model for Thermal Infrared Tracking 热红外跟踪的可逆模态转换模型

IF 3.2 4区计算机科学

IEEE MultiMedia Pub Date : 2023-07-01 DOI: 10.1109/MMUL.2023.3239136

Yufei Zha, Fan Li, Huanyu Li, Peng Zhang, Wei Huang

{"title":"Reversible Modal Conversion Model for Thermal Infrared Tracking","authors":"Yufei Zha, Fan Li, Huanyu Li, Peng Zhang, Wei Huang","doi":"10.1109/MMUL.2023.3239136","DOIUrl":"https://doi.org/10.1109/MMUL.2023.3239136","url":null,"abstract":"Learning powerful CNN representation of the target is a key issue for thermal infrared (TIR) tracking. The lack of massive training TIR data is one of the obstacles to training the network in an end-to-end way from the scratch. Compared to the time-consuming and labor-intensive method of heavily relabeling data, we obtain trainable TIR images by leveraging the massive annotated RGB images in this article. Unlike the traditional image generation models, a modal reversible module is designed to maximize the information propagation between RGB and TIR modals in this work. The advantage is that this module can preserve the modal information as possible when the network is conducted on a large number of aligned RGBT image pairs. Additionally, the fake-TIR features generated by the proposed module are also integrated to enhance the target representation ability when TIR tracking is on-the-fly. To verify the proposed method, we conduct sufficient experiments on both single-modal TIR and multimodal RGBT tracking datasets. In single-modal TIR tracking, the performance of our method is improved by 2.8% and 0.94% on success rate compared with the SOTA on LSOTB-TIR and PTB-TIR dataset. In multimodal RGBT fusion tracking, the proposed method is tested on the RGBT234 and VOT-RGBT2020 datasets and the results have also reached the performance of SOTA.","PeriodicalId":13240,"journal":{"name":"IEEE MultiMedia","volume":"30 1","pages":"8-24"},"PeriodicalIF":3.2,"publicationDate":"2023-07-01","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"48643610","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}

引用次数: 0

IEEE Computer Society Information IEEE计算机学会信息

4区计算机科学

IEEE MultiMedia Pub Date : 2023-07-01 DOI: 10.1109/mmul.2023.3308996

引用次数: 0

IEEE Transactions on Sustainable Computing IEEE可持续计算汇刊

4区计算机科学

IEEE MultiMedia Pub Date : 2023-07-01 DOI: 10.1109/mmul.2023.3313239

引用次数: 0

Computing in Science & Engineering 计算机科学& &;工程

4区计算机科学

IEEE MultiMedia Pub Date : 2023-07-01 DOI: 10.1109/mmul.2023.3311108