2022 IEEE 5th International Conference on Multimedia Information Processing and Retrieval (MIPR)最新文献_第8页

Open-Eye: An Open Platform to Study Human Performance on Identifying AI-Synthesized Faces Open- eye:一个研究人类识别人工智能合成人脸性能的开放平台

2022 IEEE 5th International Conference on Multimedia Information Processing and Retrieval (MIPR) Pub Date : 2022-05-13 DOI: 10.1109/MIPR54900.2022.00047

Hui Guo, Shu Hu, Xin Wang, Ming-Ching Chang, Siwei Lyu

引用次数: 6

License Plate Privacy in Collaborative Visual Analysis of Traffic Scenes 交通场景协同视觉分析中的车牌隐私

2022 IEEE 5th International Conference on Multimedia Information Processing and Retrieval (MIPR) Pub Date : 2022-05-03 DOI: 10.1109/MIPR54900.2022.00060

Saeed Ranjbar Alvar, Korcan Uyanik, Ivan V. Baji'c

引用次数: 3

Feature Compression for Rate Constrained Object Detection on the Edge 边缘上速率受限目标检测的特征压缩

2022 IEEE 5th International Conference on Multimedia Information Processing and Retrieval (MIPR) Pub Date : 2022-04-15 DOI: 10.1109/MIPR54900.2022.00008

Zhongzheng Yuan, Samyak Rawlekar, S. Garg, E. Erkip, Yao Wang

{"title":"Feature Compression for Rate Constrained Object Detection on the Edge","authors":"Zhongzheng Yuan, Samyak Rawlekar, S. Garg, E. Erkip, Yao Wang","doi":"10.1109/MIPR54900.2022.00008","DOIUrl":"https://doi.org/10.1109/MIPR54900.2022.00008","url":null,"abstract":"Recent advances in computer vision has led to a growth of interest in deploying visual analytics model on mobile devices. However, most mobile devices have limited computing power, which prohibits them from running large scale visual analytics neural networks. An emerging approach to solve this problem is to offload the computation of these neural networks to computing resources at an edge server. Efficient computation offloading requires optimizing the trade-off between multiple objectives including com-pressed data rate, analytics performance, and computation speed. In this work, we consider a “split computation” system to offload a part of the computation of the YOLO object detection model. We propose a learnable feature compression approach to compress the intermediate YOLO features with light-weight computation. We train the feature compression and decompression module together with the YOLO model to optimize the object detection accuracy under a rate constraint. Compared to baseline methods that apply either standard image compression or learned image compression at the mobile and perform image de-compression and YOLO at the edge, the proposed system achieves higher detection accuracy at the low to medium rate range. Furthermore, the proposed system requires sub-stantially lower computation time on the mobile device with CPU only.","PeriodicalId":228640,"journal":{"name":"2022 IEEE 5th International Conference on Multimedia Information Processing and Retrieval (MIPR)","volume":"6 1","pages":"0"},"PeriodicalIF":0.0,"publicationDate":"2022-04-15","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"128018475","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":0,"RegionCategory":"","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}

引用次数: 5

Sparse Tensor-based Point Cloud Attribute Compression 基于稀疏张量的点云属性压缩

2022 IEEE 5th International Conference on Multimedia Information Processing and Retrieval (MIPR) Pub Date : 2022-04-03 DOI: 10.1109/MIPR54900.2022.00018

Jianqiang Wang, Zhan Ma

{"title":"Sparse Tensor-based Point Cloud Attribute Compression","authors":"Jianqiang Wang, Zhan Ma","doi":"10.1109/MIPR54900.2022.00018","DOIUrl":"https://doi.org/10.1109/MIPR54900.2022.00018","url":null,"abstract":"Surveillance videos can capture a variety of realistic events and also anomalies. Due to an increase in the crime rate in public areas, surveillance cameras are adopted in a very large number. But as these crimes/public disputes are rare to occur at a specific location, human monitors are idle most of the time. Hence, there is a justified need to develop intelligent systems for anomaly detection. There are several seminal deepneural architectures proposed in this field of anomaly detection ranging from using deep learning as a feature extraction tool to complete end-to-end deep-learning-based anomaly detection models. Any practical anomaly detection model must be generic in detecting a spectrum of anomalous events; however, several models can detect only specific types of anomalies. Further, several models are not amenable to distributed training over many machines on large streaming data, which is typical in a video surveillance system. In this paper, we discuss the techniques to detect anomalies in real-time by exploring recent architectures in the literature and analyze and explore ways we can improve the detection accuracy of the model. We propose a batching methodology that improves the existing model's area under the curve by 2%.","PeriodicalId":228640,"journal":{"name":"2022 IEEE 5th International Conference on Multimedia Information Processing and Retrieval (MIPR)","volume":"57 5 1","pages":"0"},"PeriodicalIF":0.0,"publicationDate":"2022-04-03","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"129473876","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":0,"RegionCategory":"","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}

引用次数: 13

Swin-Pose: Swin Transformer Based Human Pose Estimation swwin -Pose:基于人体姿态估计的Swin变压器

2022 IEEE 5th International Conference on Multimedia Information Processing and Retrieval (MIPR) Pub Date : 2022-01-19 DOI: 10.1109/MIPR54900.2022.00048

Zinan Xiong, Chenxi Wang, Ying Li, Yan Luo, Yu Cao

引用次数: 8

Attentive Graph Neural Networks for Few-Shot Learning 关注图神经网络的少镜头学习

2022 IEEE 5th International Conference on Multimedia Information Processing and Retrieval (MIPR) Pub Date : 2020-07-14 DOI: 10.1109/MIPR54900.2022.00033

Hao Cheng, Joey Tianyi Zhou, Wee Peng Tay, B. Wen

引用次数: 6