2nd Workshop on AI for Space in conjunction with ECCV 2022: Call for Papers

2nd Workshop on AI for Space in conjunction with ECCV 2022:

AI4Space focuses on the role of AI, particularly computer vision and
machine learning, in helping to solve technical challenges related to
space, from autonomous spacecraft, space mining, debris monitoring and
mitigation, to answering fundamental questions about the universe. The
workshop will highlight the space capabilities that draw from and/or
overlap significantly with vision and learning research, outline the
unique difficulties presented by space applications to vision and
learning, and discuss recent advances towards overcoming those
obstacles.

 

Website:

https://aiforspace.github.io/2022/

 

Call for Papers:

We solicit papers for AI4Space. Papers will be reviewed and accepted
papers will be published in the proceedings of ECCV Workshops. Authors
of accepted papers will also be invited to present at the workshop (in
hybrid mode) at ECCV 2022, Tel-Aviv, late October 2022.

The general emphasis of AI4Space is vision and learning algorithms in
off-Earth environments, including in the orbital region, surface and
underground environments on other planetary bodies (e.g., the moon,
Mars and asteroids), interplanetary space and solar system, and
distant galaxies. Target application areas include autonomous
spacecraft, space robotics, space traffic management, astronomy,
astrobiology and cosmology. Emphasis is also placed on novel sensors
and processing hardware for vision and learning in space, mitigating
the challenges of the space environment towards vision and learning
(e.g., solar radiation, extreme temperatures), and solving practical
difficulties in vision and learning for space (e.g., lack of training
data, unknown or partially known characteristics of operating
environments).

 

A specific list of topics is as follows:
- Visual navigation for spacecraft operations
- Vision and learning for space robotics
- GPS-denied positioning on the moon and Mars
- Space debris monitoring and mitigation
- Vision and learning for astronomy, astrobiology and cosmology
- Novel sensors for space applications
- Processing hardware for vision and learning in space
- Mitigating challenges of the space environment to vision and learning
- Datasets, transfer learning and domain gap for space problems

 

Paper deadline:

11:59pm 17 June 2022 (tentative)

More details:

https://aiforspace.github.io/2022/