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Autonomous Navigation in Unconstrained Environments

IIIT Hyderabad in association with Intel, Bangalore; University of Maryland, College Park; NEC / University of California San Diego and IIT Hyderabad organised the 3rd Workshop on Autonomous Navigation in Unconstrained Environments. This workshop was organised in conjunction with Computer Vision and Pattern Recognition (CVPR-2021) on 19 June.

Autonomous driving has recently emerged as a keystone problem for computer vision and machine learning, with significant interest in both academia and industry. The workshop explored feasibility and directions for the next generation of vision and learning solutions that will handle such real-world challenges. Consistent with this motivation, this edition introduced a domain adaptation challenge to study semantic segmentation across driving scenes from multiple domains, where labeled data might be limited in the target domains.

This workshop also adopted a broad view of what is entailed by driving in unconstrained environments. Some aspects such as changes in weather, time of day or imaging conditions are already being studied by the community, for instance, under the purview of domain adaptation. However, these have still largely been for environments with organized traffic and favorable infrastructure. Thus, besides those aspects, this workshop also posed the challenge of autonomous driving in less constrained traffic, along with the infrastructure that is not always dependable.

 

Organizing team

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More details at: http://cvit.iiit.ac.in/autonue2021/