Proceedings of the 2nd ACM International Conference on Multimedia in Asia最新文献_第2页

Hierarchical clustering via mutual learning for unsupervised person re-identification 基于互学习的无监督人再识别层次聚类

Proceedings of the 2nd ACM International Conference on Multimedia in Asia Pub Date : 2021-03-07 DOI: 10.1145/3444685.3446268

Xu Xu, Liyan Zhang, Zhaomeng Huang, Guodong Du

{"title":"Hierarchical clustering via mutual learning for unsupervised person re-identification","authors":"Xu Xu, Liyan Zhang, Zhaomeng Huang, Guodong Du","doi":"10.1145/3444685.3446268","DOIUrl":"https://doi.org/10.1145/3444685.3446268","url":null,"abstract":"Person re-identification (re-ID) aims to establish identity correspondence across different cameras. State-of-the-art re-ID approaches are mainly clustering-based Unsupervised Domain Adaptation (UDA) methods, which attempt to transfer the model trained on the source domain to target domain, by alternatively generating pseudo labels by clustering target-domain instances and training the network with generated pseudo labels to perform feature learning. However, these approaches suffer from the problem of inevitable label noise caused by the clustering procedure that dramatically impact the model training and feature learning of the target domain. To address this issue, we propose an unsupervised Hierarchical Clustering via Mutual Learning (HCML) framework, which can jointly optimize the dual training network and the clustering procedure to learn more discriminative features from the target domain. Specifically, the proposed HCML framework can effectively update the hard pseudo labels generated by clustering process and soft pseudo label generated by the training network both in on-line manner. We jointly adopt the repelled loss, triplet loss, soft identity loss and soft triplet loss to optimize the model. The experimental results on Market-to-Duke, Duke-to-Market, Market-to-MSMT and Duke-to-MSMT unsupervised domain adaptation tasks have demonstrated the superiority of our proposed HCML framework compared with other state-of-the-art methods.","PeriodicalId":119278,"journal":{"name":"Proceedings of the 2nd ACM International Conference on Multimedia in Asia","volume":"1 1","pages":"0"},"PeriodicalIF":0.0,"publicationDate":"2021-03-07","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"122002867","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: 0

Change detection from SAR images based on deformable residual convolutional neural networks 基于可变形残差卷积神经网络的SAR图像变化检测

Proceedings of the 2nd ACM International Conference on Multimedia in Asia Pub Date : 2021-03-07 DOI: 10.1145/3444685.3446320

Junjie Wang, Feng Gao, Junyu Dong

{"title":"Change detection from SAR images based on deformable residual convolutional neural networks","authors":"Junjie Wang, Feng Gao, Junyu Dong","doi":"10.1145/3444685.3446320","DOIUrl":"https://doi.org/10.1145/3444685.3446320","url":null,"abstract":"Convolutional neural networks (CNN) have made great progress for synthetic aperture radar (SAR) images change detection. However, sampling locations of traditional convolutional kernels are fixed and cannot be changed according to the actual structure of the SAR images. Besides, objects may appear with different sizes in natural scenes, which requires the network to have stronger multi-scale representation ability. In this paper, a novel Deformable Residual Convolutional Neural Network (DRNet) is designed for SAR images change detection. First, the proposed DRNet introduces the deformable convolutional sampling locations, and the shape of convolutional kernel can be adaptively adjusted according to the actual structure of ground objects. To create the deformable sampling locations, 2-D offsets are calculated for each pixel according to the spatial information of the input images. Then the sampling location of pixels can adaptively reflect the spatial structure of the input images. Moreover, we proposed a novel pooling module replacing the vanilla pooling to utilize multi-scale information effectively, by constructing hierarchical residual-like connections within one pooling layer, which improve the multi-scale representation ability at a granular level. Experimental results on three real SAR datasets demonstrate the effectiveness of the proposed DR-Net.","PeriodicalId":119278,"journal":{"name":"Proceedings of the 2nd ACM International Conference on Multimedia in Asia","volume":"174 1","pages":"0"},"PeriodicalIF":0.0,"publicationDate":"2021-03-07","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"123204324","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: 3

A multimedia solution to motivate childhood cancer patients to keep up with cancer treatment 一个多媒体解决方案，激励儿童癌症患者跟上癌症治疗

Proceedings of the 2nd ACM International Conference on Multimedia in Asia Pub Date : 2021-03-07 DOI: 10.1145/3444685.3446262

Carmen Chai Wang Er, B. Lau, A. Mahmud, Mark Tee Kit Tsun

{"title":"A multimedia solution to motivate childhood cancer patients to keep up with cancer treatment","authors":"Carmen Chai Wang Er, B. Lau, A. Mahmud, Mark Tee Kit Tsun","doi":"10.1145/3444685.3446262","DOIUrl":"https://doi.org/10.1145/3444685.3446262","url":null,"abstract":"Childhood cancer is a deadly illness that requires the young patient to adhere to cancer treatment for survival. Sadly, the high treatment side-effect burden can make it difficult for patients to keep up with their treatment. However, childhood cancer patients can manage these treatment side effects through daily self-care to make the process more bearable. This paper outlines the design and development process of a multimedia-based solution to motivate these young patients to adhere to cancer treatment and manage their treatment side effects. Due to the high appeal of multimedia-based interventions and the proficiency of young children in using mobile devices, the intervention of this study takes the form of a virtual pet serious game developed for mobile. The intervention which is developed based on the Protection Motivation Theory, includes multiple game modules with the purpose of improving the coping appraisal of childhood cancer patients on using cancer treatment to fight cancer, and taking daily self-care to combat treatment side-effects. The prototype testing results show that the intervention is well received by the voluntary play testers. Future work of this study includes the evaluation of the intervention developed with childhood cancer patients to determine its effectiveness.","PeriodicalId":119278,"journal":{"name":"Proceedings of the 2nd ACM International Conference on Multimedia in Asia","volume":"9 1","pages":"0"},"PeriodicalIF":0.0,"publicationDate":"2021-03-07","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"129274021","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: 2

Multi-level expression guided attention network for referring expression comprehension 多层次表达引导注意网络对表达理解的参考作用

Proceedings of the 2nd ACM International Conference on Multimedia in Asia Pub Date : 2021-03-07 DOI: 10.1145/3444685.3446270

Liang Peng, Yang Yang, Xing Xu, Jingjing Li, Xiaofeng Zhu

{"title":"Multi-level expression guided attention network for referring expression comprehension","authors":"Liang Peng, Yang Yang, Xing Xu, Jingjing Li, Xiaofeng Zhu","doi":"10.1145/3444685.3446270","DOIUrl":"https://doi.org/10.1145/3444685.3446270","url":null,"abstract":"Referring expression comprehension is a task of identifying a text-related object or region in a given image by a natural language expression. In this task, it is essential to understand the expression sentence in multi-aspect and adapt it to region representations for generating the discriminative information. Unfortunately, previous approaches usually focus on the important words or phrases in the expression using self-attention mechanisms, which causes that they may fail to distinguish the target region from others, especially the similar regions. To address this problem, we propose a novel model, termed Multi-level Expression Guided Attention network (MEGA-Net). It contains a multi-level visual attention schema guided by the expression representations in different levels, i.e., sentence-level, word-level and phrase-level, which allows generating the discriminative region features and helps to locate the related regions accurately. In addition, to distinguish the similar regions, we design a two-stage structure, where we first select top-K candidate regions according to their matching scores in the first stage, then we apply an object comparison attention mechanism to learn the difference between the candidates for matching the target region. We evaluate the proposed approach on three popular benchmark datasets and the experimental results demonstrate that our model performs against state-of-the-art methods.","PeriodicalId":119278,"journal":{"name":"Proceedings of the 2nd ACM International Conference on Multimedia in Asia","volume":"12 1","pages":"0"},"PeriodicalIF":0.0,"publicationDate":"2021-03-07","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"128484854","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: 2

Fixations based personal target objects segmentation 基于个人目标对象分割的注视

Proceedings of the 2nd ACM International Conference on Multimedia in Asia Pub Date : 2021-03-07 DOI: 10.1145/3444685.3446310

Ran Shi, Gongyang Li, Weijie Wei, Zhi Liu

{"title":"Fixations based personal target objects segmentation","authors":"Ran Shi, Gongyang Li, Weijie Wei, Zhi Liu","doi":"10.1145/3444685.3446310","DOIUrl":"https://doi.org/10.1145/3444685.3446310","url":null,"abstract":"With the development of the eye-tracking technique, the fixation becomes an emergent interactive mode in many human-computer interaction study field. For a personal target objects segmentation task, although the fixation can be taken as a novel and more convenient interactive input, it induces a heavy ambiguity problem of the input's indication so that the segmentation quality is severely degraded. In this paper, to address this challenge, we develop an \"extraction-to-fusion\" strategy based iterative lightweight neural network, whose input is composed by an original image, a fixation map and a position map. Our neural network consists of two main parts: The first extraction part is a concise interlaced structure of standard convolution layers and progressively higher dilated convolution layers to better extract and integrate local and global features of target objects. The second fusion part is a convolutional long short-term memory component to refine the extracted features and store them. Depending on the iteration framework, current extracted features are refined by fusing them with stored features extracted in the previous iterations, which is a feature transmission mechanism in our neural network. Then, current improved segmentation result is generated to further adjust the fixation map and the position map in the next iteration. Thus, the ambiguity problem induced by the fixations can be alleviated. Experiments demonstrate better segmentation performance of our method and effectiveness of each part in our model.","PeriodicalId":119278,"journal":{"name":"Proceedings of the 2nd ACM International Conference on Multimedia in Asia","volume":"101 1","pages":"0"},"PeriodicalIF":0.0,"publicationDate":"2021-03-07","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"130081852","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: 1

Storyboard relational model for group activity recognition 小组活动识别的故事板关系模型

Proceedings of the 2nd ACM International Conference on Multimedia in Asia Pub Date : 2021-03-07 DOI: 10.1145/3444685.3446255

Boning Li, Xiangbo Shu, Rui Yan

引用次数: 5

Objective object segmentation visual quality evaluation based on pixel-level and region-level characteristics 基于像素级和区域级特征的目标分割视觉质量评价

Proceedings of the 2nd ACM International Conference on Multimedia in Asia Pub Date : 2021-03-07 DOI: 10.1145/3444685.3446305

Ran Shi, Jian Xiong, T. Qiao

{"title":"Objective object segmentation visual quality evaluation based on pixel-level and region-level characteristics","authors":"Ran Shi, Jian Xiong, T. Qiao","doi":"10.1145/3444685.3446305","DOIUrl":"https://doi.org/10.1145/3444685.3446305","url":null,"abstract":"Objective object segmentation visual quality evaluation is an emergent member of the visual quality assessment family. It aims at developing an objective measure instead of a subjective survey to evaluate the object segmentation quality in agreement with human visual perception. It is an important benchmark to assess and compare performances of object segmentation methods in terms of the visual quality. In spite of its essential role, it still lacks of sufficient studying compared with other visual quality evaluation researches. In this paper, we propose a novel full-reference objective measure including a pixel-level sub-measure and a region-level sub-measure. For the pixel-level sub-measure, it assigns proper weights to not only false positive pixels and false negative pixels but also true positive pixels according to their certainty degrees. For the region-level sub-measure, it considers location distribution of the false negative errors and correlations among neighboring pixels. Thus, by combining these two sub-measures, our measure can evaluate similarity of area, shape and object completeness between one segmentation result and its ground truth in terms of human visual perception. In order to evaluate the performance of our proposed measure, we tested it on an object segmentation subjective visual quality assessment database. The experimental results demonstrate that our proposed measure with good robustness performs better in matching subjective assessments compared with other state-of-the-art objective measures.","PeriodicalId":119278,"journal":{"name":"Proceedings of the 2nd ACM International Conference on Multimedia in Asia","volume":"31 1","pages":"0"},"PeriodicalIF":0.0,"publicationDate":"2021-03-07","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"114045525","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: 1

Fusing CAMs-weighted features and temporal information for robust loop closure detection 融合cam加权特征和时间信息的鲁棒闭环检测

Proceedings of the 2nd ACM International Conference on Multimedia in Asia Pub Date : 2021-03-07 DOI: 10.1145/3444685.3446309

Yao Li, S. Zhong, Tongwei Ren, Y. Liu

{"title":"Fusing CAMs-weighted features and temporal information for robust loop closure detection","authors":"Yao Li, S. Zhong, Tongwei Ren, Y. Liu","doi":"10.1145/3444685.3446309","DOIUrl":"https://doi.org/10.1145/3444685.3446309","url":null,"abstract":"As a key component in simultaneous localization and mapping (SLAM) system, loop closure detection (LCD) eliminates the accumulated errors by recognizing previously visited places. In recent years, deep learning methods have been proved effective in LCD. However, most of the existing methods do not make good use of the useful information provided by monocular images, which tends to limit their performance in challenging dynamic scenarios with partial occlusion by moving objects. To this end, we propose a novel workflow, which is able to combine multiple information provided by images. We first introduce semantic information into LCD by developing a local-aware Class Activation Maps (CAMs) weighting method for extracting features, which can reduce the adverse effects of moving objects. Compared with previous methods based on semantic segmentation, our method has the advantage of not requiring additional models or other complex operations. In addition, we propose two effective temporal constraint strategies, which utilize the relationship of image sequences to improve the detection performance. Moreover, we propose to use the keypoint matching strategy as the final detector to further refuse false positives. Experiments on four publicly available datasets indicate that our approach can achieve higher accuracy and better robustness than the state-of-the-art methods.","PeriodicalId":119278,"journal":{"name":"Proceedings of the 2nd ACM International Conference on Multimedia in Asia","volume":"2005 1","pages":"0"},"PeriodicalIF":0.0,"publicationDate":"2021-03-07","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"116898427","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: 0

Distilling knowledge in causal inference for unbiased visual question answering 为无偏视觉问答提取因果推理中的知识

Proceedings of the 2nd ACM International Conference on Multimedia in Asia Pub Date : 2021-03-07 DOI: 10.1145/3444685.3446256

Yonghua Pan, Zechao Li, Liyan Zhang, Jinhui Tang

{"title":"Distilling knowledge in causal inference for unbiased visual question answering","authors":"Yonghua Pan, Zechao Li, Liyan Zhang, Jinhui Tang","doi":"10.1145/3444685.3446256","DOIUrl":"https://doi.org/10.1145/3444685.3446256","url":null,"abstract":"Current Visual Question Answering (VQA) models mainly explore the statistical correlations between answers and questions, which fail to capture the relationship between the visual information and answers. The performance dramatically decreases when the distribution of handled data is different from the training data. Towards this end, this paper proposes a novel unbiased VQA model by exploring the Casual Inference with Knowledge Distillation (CIKD) to reduce the influence of bias. Specifically, the causal graph is first constructed to explore the counterfactual causality and infer the casual target based on the causal effect, which well reduces the bias from questions and obtain answers without training. Then knowledge distillation is leveraged to transfer the knowledge of the inferred casual target to the conventional VQA model. It makes the proposed method enable to handle both the biased data and standard data. To address the problem of the bad bias from the knowledge distillation, the ensemble learning is introduced based on the hypothetical bias reason. Experiments are conducted to show the performance of the proposed method. The significant improvements over the state-of-the-art methods on the VQA-CP v2 dataset well validate the contributions of this work.","PeriodicalId":119278,"journal":{"name":"Proceedings of the 2nd ACM International Conference on Multimedia in Asia","volume":"21 1","pages":"0"},"PeriodicalIF":0.0,"publicationDate":"2021-03-07","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"114338947","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: 9

Global and local feature alignment for video object detection 视频目标检测的全局和局部特征对齐

Proceedings of the 2nd ACM International Conference on Multimedia in Asia Pub Date : 2021-03-07 DOI: 10.1145/3444685.3446263

Haihui Ye, Qiang Qi, Ying Wang, Yang Lu, Hanzi Wang

{"title":"Global and local feature alignment for video object detection","authors":"Haihui Ye, Qiang Qi, Ying Wang, Yang Lu, Hanzi Wang","doi":"10.1145/3444685.3446263","DOIUrl":"https://doi.org/10.1145/3444685.3446263","url":null,"abstract":"Extending image-based object detectors into video domain suffers from immense inadaptability due to the deteriorated frames caused by motion blur, partial occlusion or strange poses. Therefore, the generated features of deteriorated frames encounter the poor quality of misalignment, which degrades the overall performance of video object detectors. How to capture valuable information locally or globally is of importance to feature alignment but remains quite challenging. In this paper, we propose a Global and Local Feature Alignment (abbreviated as GLFA) module for video object detection, which can distill both global and local information to excavate the deep relationship between features for feature alignment. Specifically, GLFA can model the spatial-temporal dependencies over frames based on propagating global information and capture the interactive correspondences within the same frame based on aggregating valuable local information. Moreover, we further introduce a Self-Adaptive Calibration (SAC) module to strengthen the semantic representation of features and distill valuable local information in a dual local-alignment manner. Experimental results on the ImageNet VID dataset show that the proposed method achieves high performance as well as a good trade-off between real-time speed and competitive accuracy.","PeriodicalId":119278,"journal":{"name":"Proceedings of the 2nd ACM International Conference on Multimedia in Asia","volume":"35 1","pages":"0"},"PeriodicalIF":0.0,"publicationDate":"2021-03-07","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"131565458","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: 0