1st Workshop on 3D-VAST

From street to space: 3D Vision AcrosS alTitudes

ICCV 2025 Workshop



Introduction

As large-scale 3D scene modeling becomes increasingly important for applications such as urban planning, robotics, autonomous navigation, and virtual simulations, the need for diverse, high-quality visual data is greater than ever. However, acquiring dense and high-resolution ground-level imagery at scale is often impractical due to access limitations, cost, and environmental variability. In contrast, aerial and satellite imagery provide broader spatial coverage but lack the fine-grained details needed for many downstream applications. Combining images from multiple altitudes — from ground cameras to aerial drones and satellites—offers a promising solution to overcome these limitations, enabling richer, more complete 3D reconstructions.

How can we achieve coherent and accurate 3D scene modeling when our visual world is captured from vastly different altitudes—ground, aerial, and satellite—under varying conditions? Each altitude offers distinct advantages, but cross-altitude data fusion introduces significant challenges: sparse and incomplete views, visual ambiguities, spatio-temporal inconsistencies, image quality variations, dynamic scene changes, and environmental factors that alter topology over time. Traditional 3D reconstruction methods, optimized for dense and structured inputs, struggle with such heterogeneous multi-altitude data. Advances in multi-scale feature alignment, neural scene representations, and robust cross-view fusion offer promising solutions, but key challenges remain.


Call For Papers

Call for papers: We invite non-archival papers of up to 8 pages (in ICCV format) for work on tasks related to cross-altitude 3D scene modeling, understanding, rendering, and synthesis. Paper topics may include, but are not limited to:

  • Cross-altitude feature matching and registration
  • View synthesis from sparse and heterogeneous data sources
  • Sparse-view 3D reconstruction (with known or unknown camera poses)
  • Generative approaches for view completion and prediction
  • Datasets and benchmarks for evaluating cross-altitude vision systems
  • Real-world applications in urban planning, simulation, and digital twins

While the workshop focuses on 3D vision across different altitudes, the paper topic could center on a specific data source, such as outdoor ground-level, aerial-level, or indoor environments.

Submission: We encourage submissions of up to 8 pages, excluding references and acknowledgements. The submission should be in the ICCV format. Reviewing will be double-blind. Please submit your paper to the following address by the deadline: Submission Portal



Important Dates

First Round (for papers which aim to be published in the ICCV proceeding)
Paper submission deadline June 5th, 2025
Notifications to accepted papers June 24th, 2025
Paper camera ready TBD
Second Round (for papers which do not aim to be included in the ICCV proceedings, but will be presented in the workshop)
Paper submission deadline July 5th, 2025
Notifications to accepted papers July 24th, 2025
Paper camera ready TBD
Workshop date TBD


Schedule

Workshop Kickoff and Opening Comments 8:30am - 8:35am
First Keynote Speech 8:35am - 9:05am
Second Keynote Speech 9:05am - 9:35am
Third Keynote Speech 9:35am - 10:05am
Coffee Break and Poster Session 10:05am - 11:00am
Forth Keynote Speech 11:00am - 11:30am
Fifth Keynote Speech 11:30am - 12:00am


Invited Speakers


Torsten Sattler is a Senior Researcher at CTU, where he heads the Spatial Intelligence group. His work is in the intersection of 3D computer vision and machine learning, with the goal of making 3D computer vision algorithms such as 3D reconstruction and visual localization more robust and reliable through scene understanding. Torsten has (co-)organized tutorials and workshops on visual localization at the main computer vision conference, was a program chair for DAGM GCPR’20, a general chair for 3DV’22, and a program chair for ICCV’24.


Angela Dai is an Associate Professor at Technical University of Munich, where she leads the 3D AI group. Her research focuses on understanding how the 3D world can be modeled. Her research has been recognized through an ERC Starting Grant, Eurographics Young Researcher Award, Google Research Scholar Award, ZDB Junior Research Group Award, an ACM SIGGRAPH Outstanding Doctoral Dissertation Honorable Mention, as well as a Stanford Graduate Fellowship.


Noah Snavely is a Professor of Computer Science at Cornell Tech interested. He also works at Google DeepMind in NYC. His research interests are in computer vision and graphics, in particular in 3D understanding and depiction of scenes from images. Noah is the recipient of a PECASE, a Microsoft New Faculty Fellowship, an Alfred P. Sloan Fellowship, and a SIGGRAPH Significant New Researcher Award, and is a Fellow of the ACM and the IEEE.


Nathan Jacobs is a Professor at Washington University in St. Louis. His current focus is developing techniques for mining information about the natural world from geotagged imagery, including images from social networks, publicly available outdoor webcams, and satellites. His research has been funded by NSF, NIH, DARPA, IARPA, NGA, ARL, AFRL, and Google.


Jingyi Yu is a Chair Professor and the Vice Provost of ShanghaiTech University. He also serves as the Dean of the School of Information Science and Technology at ShanghaiTech University. His research interests span a range of topics in computer vision and computer graphics, especially on computational photography and non-conventional optics and camera designs. He is a recipient of the NSF CAREER Award, the AFOSR YIP Award, and the Outstanding Junior Faculty Award at the University of Delaware.


Organizers

Yujiao Shi
Assistant Professor, ShanghaiTech University
Yuanbo Xiangli
Postdoctoral Researcher, Cornell University
Zuzana Kukelova
Assistant Professor, Czech Technical University
Bo Dai
Assistant Professor, The University of Hong Kong
Richard Hartley
Distinguished Professor Emeritus, ANU
Hongdong Li
Professor, Australian National University



Contact

To contact the organizers please use shiyj2@shanghaitech.edu.cn,com



Acknowledgments

Thanks to visualdialog.org for the webpage format.