The overarching goal of this workshop is to gather researchers, students, and advocates who work at the intersection of accessibility, computer vision, and autonomous systems. We plan to use the workshop to identify challenges and pursue solutions for the current lack of shared and principled development tools for data-driven vision-based accessibility systems. For instance, there is a general lack of vision-based benchmarks and methods relevant to accessibility (e.g., people with disabilities and mobility aids are currently mostly absent from large-scale datasets in pedestrian detection). Our workshop will provide a unique opportunity for fostering a mutual discussion between accessibility, computer vision, and robotics researchers and practitioners.

Coming soon ...

As an updated challenge for 2024, we release the following:

1. Training, validation, and testing data, which can be found in this link
2. An evaluation server for instance segmentation and for pose estimation.

More info on data and submission can be found in the eval.ai links above. Note that the data this year includes both instance segmentation and pose estimation challenge. Moreover, we provide access to temporal history and LiDAR data for each image.
The challenge builds on our prior workshop's synthetic instance segmentation benchmark with mobility aids (see Zhang et al., X-World: Accessibility, Vision, and Autonomy Meet, ICCV 2021 bit.ly/2X8sYoX). The benchmark contains challenging accessibility-related person and object categories, such as `cane' and `wheelchair.' We aim to use the challenge to uncover research opportunities and spark the interest of computer vision and AI researchers working on more robust visual reasoning models for accessibility.
The team with the top performing submission will be invited to give short talks during the workshop and will receive a financial award of $500 and an OAK—D camera (We thank the National Science Foundation, US Department of Transportation's Inclusive Design Challenge and Intel for their support for these awards)

We encourage submission of relevant research (including work in progress, novel perspectives, formative studies, benchmarks, methods) as extended abstracts for the poster session and workshop discussion (up to 4 pages in CVPR format, not including references). CVPR Overleaf template can be found here. Latex/Word templates can be found here. Please send your extended abstracts to mobility@bu.edu. Note that submissions do not need to be anonymized. Extended abstracts of already published works can also be submitted. Accepted abstracts will be presented at the poster session, and will not be included in the printed proceedings of the workshop. Topics of interests by this workshop include, but are not limited to:

1. AI for Accessibility
2. Accessibility-Centered Computer Vision Tasks and Datasets
3. Data-Driven Accessibility Tools, Metrics and Evaluation Frameworks
4. Practical Challenges in Ability-Based Assistive Technologies
5. Accessibility in Robotics and Autonomous Vehicles
6. Long-Tail and Low-Shot Recognition of Accessibility-Based Tasks
7. Accessible Homes, Hospitals, Cities, Infrastructure, Transportation
8. Crowdsourcing and Annotation Tools for Vision and Accessibility
9. Empirical Real-World Studies in Inclusive System Design
10. Assistive Human-Robot Interaction
11. Remote Accessibility Systems
12. Multi-Modal (Audio, Visual, Inertial, Haptic) Learning and Interaction
13. Accessible Mobile and Information Technologies
14. Virtual, Augmented, and Mixed Reality for Accessibility
15. Novel Designs for Robotic, Wearable and Smartphone-Based Assistance
16. Intelligent Assistive Embodied and Navigational Agents
17. Socially Assistive Mobile Applications
18. Human-in-the-Loop Machine Learning Techniques
19. Accessible Tutoring and Education
20. Personalization for Diverse Physical, Motor, and Cognitive Abilities
21. Embedded Hardware-Optimized Assistive Systems
22. Intelligent Robotic Wheelchairs
23. Medical and Social and Cultural Models of Disability
24. New Frameworks for Taxonomies and Terminology