3D Computer Vision for Remote Sensing: Point Clouds, Reconstruction and Scene Understanding

Dear Colleagues,

Recent advances in remote sensing technology have yielded unprecedented volumes of Earth observation data. Simultaneously, the emergence of big data has spurred rapid advances in 3D computer vision, demonstrating significant potential to convert raw remote sensing observations into rich, actionable 3D representations of our environment. However, most existing 3D computer vision research has centered on general computer vision benchmarks, with limited direct adaptation to the distinctive nature of remote sensing data. Large-scale 3D reconstruction, which aims to transform original remote sensing observations into coherent, complete, and structurally meaningful 3D models, remains a significant challenge. Consequently, generating scalable, semantically consistent, and physically plausible 3D representations from large-scale remote sensing data remains an open and critical research problem.

To advance research in the field of remote sensing, we are pleased to announce this Call for Papers, inviting contributions on cutting-edge techniques for 3D point cloud processing, reconstruction, and scene understanding. Topics of interest include, but are not limited to:

• Novel theories, algorithms, and techniques for large-scale 3D point cloud processing, scene understanding, and reconstruction;
• Multimodal data fusion methods and benchmark datasets for 3D remote sensing applications;
• Large vision–language models applied to 3D remote sensing tasks such as scene understanding, reconstruction, and visual question answering;
• Deep generative models for 3D point cloud synthesis and reconstruction;
• 3D reconstruction of indoor and outdoor environments, cultural heritage sites, and urban or natural landscapes.

Dr. Hanyun Wang
Dr. Li Li
Guest Editors

Dr. Qi Dong
Dr. Yao Wei
Guest Editor Assistants

Manuscript Submission Information

Manuscripts should be submitted online at www.mdpi.com by registering and logging in to this website. Once you are registered, click here to go to the submission form. Manuscripts can be submitted until the deadline. All submissions that pass pre-check are peer-reviewed. Accepted papers will be published continuously in the journal (as soon as accepted) and will be listed together on the special issue website. Research articles, review articles as well as short communications are invited. For planned papers, a title and short abstract (about 250 words) can be sent to the Editorial Office for assessment.

Submitted manuscripts should not have been published previously, nor be under consideration for publication elsewhere (except conference proceedings papers). All manuscripts are thoroughly refereed through a single-anonymized peer-review process. A guide for authors and other relevant information for submission of manuscripts is available on the Instructions for Authors page. Remote Sensing is an international peer-reviewed open access semimonthly journal published by MDPI.

Please visit the Instructions for Authors page before submitting a manuscript. The Article Processing Charge (APC) for publication in this open access journal is 2700 CHF (Swiss Francs). Submitted papers should be well formatted and use good English. Authors may use MDPI's English editing service prior to publication or during author revisions.