The goal of RGB-D salient object detection is to aggregate the information of the two modalities of RGB and depth to accurately detect and segment salient objects. Existing RGB-D SOD models can extract the multilevel features of single modality well and can also integrate cross-modal features, but it can rarely handle both at the same time. To tap into and make the most of the correlations of intra- and inter-modality information, in this paper, we proposed an attention-guided cross-modal multi-feature aggregation network for RGB-D SOD. Our motivation was that both cross-modal feature fusion and multilevel feature fusion are crucial for RGB-D SOD task. The main innovation of this work lies in two points: One is the cross-modal pyramid feature interaction (CPFI) module that integrates multilevel features from both RGB and depth modalities in a bottom-up manner, and the other is cross-modal feature decoder (CMFD) that aggregates the fused features to generate the final saliency map. Extensive experiments on six benchmark datasets showed that the proposed attention-guided cross-modal multiple feature aggregation network (ACFPA-Net) achieved competitive performance over 15 state of the art (SOTA) RGB-D SOD methods, both qualitatively and quantitatively.
Citation: Bojian Chen, Wenbin Wu, Zhezhou Li, Tengfei Han, Zhuolei Chen, Weihao Zhang. Attention-guided cross-modal multiple feature aggregation network for RGB-D salient object detection[J]. Electronic Research Archive, 2024, 32(1): 643-669. doi: 10.3934/era.2024031
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The goal of RGB-D salient object detection is to aggregate the information of the two modalities of RGB and depth to accurately detect and segment salient objects. Existing RGB-D SOD models can extract the multilevel features of single modality well and can also integrate cross-modal features, but it can rarely handle both at the same time. To tap into and make the most of the correlations of intra- and inter-modality information, in this paper, we proposed an attention-guided cross-modal multi-feature aggregation network for RGB-D SOD. Our motivation was that both cross-modal feature fusion and multilevel feature fusion are crucial for RGB-D SOD task. The main innovation of this work lies in two points: One is the cross-modal pyramid feature interaction (CPFI) module that integrates multilevel features from both RGB and depth modalities in a bottom-up manner, and the other is cross-modal feature decoder (CMFD) that aggregates the fused features to generate the final saliency map. Extensive experiments on six benchmark datasets showed that the proposed attention-guided cross-modal multiple feature aggregation network (ACFPA-Net) achieved competitive performance over 15 state of the art (SOTA) RGB-D SOD methods, both qualitatively and quantitatively.
AIMS Energy is an Open Access international journal devoted to publishing peer-reviewed, high quality, original papers in the field of Energy science and technology, to promote the worldwide better understanding of full spectra of energy issues. Together with the Editorial Office of AIMS Energy, I wish to testify my sincere gratitude to all authors, members of the editorial board, and peer reviewers for their contribution to AIMS Energy in 2022.
In 2022, we had received 247 manuscripts, of which 58 have been accepted and published. These published papers include 40 research articles, 12 review articles, 4 editorial, and 2 opinion papers. The authors of the manuscripts are from more than 35 countries worldwide. The sources of the submissions showed a significant increase in international collaborations on the research of Energy technologies.
One of the important strategies of attracting high quality and high impact papers to our journal has been the calls for special issues. In 2022, 10 special issues were planned and called, and four of which have already published five high quality articles so far. Currently, there are 10 special issues open, and we expect to collect excellent articles for publication. AIMS Energy has 102 enthusiastic members on the editorial board, and 16 of them just joined in 2022. We will continue to renew and accept dedicated researchers to join the Editorial Board in 2023. Our members are active researchers, and we are confident that, with their dedicated effort, the journal will offer our readers more impactful publications.
With the high demand on innovative research for renewable energy and efficient utilization of energy, we expect to receive and collect more excellent articles being submitted to AIMS Energy in 2023. We would also like our members of the editorial board to encourage more of the peer researchers to publish papers and support AIMS Energy. The journal will dedicate to publishing high quality papers by both regular issues and special issues organized by the members of the editorial board. We believe that all these efforts will increase the impact and citations of the papers published by AIMS Energy.
Wish the best 2023 to our dedicated editorial board members, authors, peer reviewers, and staff members of the Editorial Office of AIMS Energy.
Prof. Peiwen (Perry) Li, Editor in Chief
AIMS Energy
Dept. of Aerospace and Mechanical Engineering,
University of Arizona, USA
The three-year manuscript statistics are shown below. In 2022, AIMS Energy published 6 issues, a total of 58 articles were published online, and the categories of published articles are as follows:
| Type | Number |
| Research Article | 40 |
| Review | 12 |
| Editorial | 4 |
| Opinion Paper | 2 |
|
Peer Review Rejection rate: 56%
Publication time (from submission to online): 90 days
An important part of our strategy of attracting high quality papers has been the call and preparation of special issues. In 2022, ten special issues were called by the editoral board members. Listed below are some examples of issues that have more than 5 papers. We encourage Editorial Board members to propose more potential topics, and to act as editors of special issues.
| Title | Link | Number of published |
| Analyzing energy storage systems for the applications of renewable energy sources | https://www.aimspress.com/aimse/article/6042/special-articles | 6 |
| Current Status and Future Prospects of Biomass Energy | https://www.aimspress.com/aimse/article/5988/special-articles | 5 |
| Hybrid renewable energy system design | https://www.aimspress.com/aimse/article/6313/special-articles | 5 |
AIMS Energy has Editorial Board members representing researchers from 23 countries, which are shown below.
We are constantly assembling the editorial board to be representative to a variety of disciplines across the field of Energy. AIMS Energy has 102 members now, and 16 of them joined in 2022. We will continue to invite dedicated experts and researchers, in order to renew the Editorial Board in 2023.
|
In the last few years, our journal has developed much faster than before; we received more than 200 manuscript submissions and published 58 papers in 2022. We have added 16 new Editorial Board members, and called for 10 special issues in 2022.
The growth of our journal will require us to invite dedicated and prestigious researchers and experts to our Editorial Board. Keeping this in mind, our first action in 2023 is to renew and rotate members of the Editorial Board. The foremost task is to invite more high-quality articles (Research and Review); especially the review articles to provide readers broad views on the technologies that interest us. We would like to increase the diversity of high-quality articles from all around the world. To set a goal, we would like to publish 60 high-quality articles in 2023. We hope Editorial Board members could help us invite some reputational scholars in your network and field to contribute articles to our journal.
Lastly, we would like to invite our board members to try to increase the influence and impact of AIMS Energy by soliciting and advertising high quality articles and special issues.
We really appreciate the time and effort of all our Editorial Board Members and Guest Editors, as well as our reviewers devoted to our journal in the difficult circumstances we have had in the last three years. All your excellent professional effort and expertise has provided us with very useful and professional suggestions in 2022. Last, but not least, thanks are given to the hard work of the in-house editorial team.
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Figures(6) / Tables(4)
Bojian Chen, Wenbin Wu, Zhezhou Li, Tengfei Han, Zhuolei Chen, Weihao Zhang. Attention-guided cross-modal multiple feature aggregation network for RGB-D salient object detection[J]. Electronic Research Archive, 2024, 32(1): 643-669. doi: 10.3934/era.2024031
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