Call for Papers

Author Guidelines

WAM-AD accepts archival regular papers of 5–8 pages (including references). Submissions should follow the same formatting requirements as WACV 2027 main-conference papers and will undergo double-blind peer review.

1. Submission Site: Papers should be submitted via OpenReview: https://openreview.net/group?id=thecvf.com/WACV/2027/Workshop/WAM-AD
2. Workshop Website: 1st WAM-AD Workshop at WACV 2027
3. Proceedings: Accepted papers will appear in the WACV 2027 Workshop Proceedings.

Regular Papers: Manuscripts of 5–8 pages, including references. Every accepted paper will receive a 10-minute oral presentation slot, including Q&A.

Other Submission Details

• Authorship Changes:
  • After the submission deadline, the list of authors will be considered final.
  • New authors cannot be added, and authors cannot be removed.
  • Changes to the authorship order will only be permitted in exceptional circumstances.
• Submission Requirements:
  • Maximum abstract size: 4000 characters.
  • Paper format: PDF only (maximum size: 20MB). Ensure your paper meets the formatting and anonymity requirements.
• Anonymity: Submissions that are not properly anonymized, do not use the WACV template, or exceed eight pages (including references) may be rejected without review.

Code Submission and Reproducibility

To improve reproducibility in AI research, we highly encourage authors to voluntarily submit their code as part of the supplementary material.

• Use the Reproducibility Checklist as a guide for writing reproducible papers.
• Reviewers are encouraged to check submitted code to ensure the trustworthiness and reproducibility of the paper’s results.
• The code must be anonymized (e.g., remove author names and institutions, including in license/copyright statements).
• Include clear instructions for setting up the environment and running the code.
• The code should cover the main results and as many minor experiments as possible.
• All submitted code and data will be reviewed confidentially and kept private.

Topics

The WAM-AD committee invites research paper submissions on topics including but not limited to:

• Action-conditioned traffic-scene prediction, counterfactual simulation, and generative driving world models
• Cascaded and joint World Action Model architectures
• Vision-Language-Action (VLA) models for perception, prediction, planning, and control
• 3D/4D scene, occupancy, map, and agent representations; dynamics and traffic-rule reasoning
• Model-based planning, reinforcement/imitation learning, memory, and long-horizon closed-loop driving
• Scalable data engines, digital twins, synthetic corner cases, and simulation-to-reality transfer
• Driving datasets, benchmarks, and metrics for visual fidelity, physical consistency, safety, and task success
• Uncertainty, causal reasoning, interpretability, robustness, human-vehicle interaction, and oversight
• Efficient on-vehicle WAMs, connected/cooperative driving, and transfer across vehicle platforms

Call for Speakers

We invite researchers and industry experts to share their work on world action models, autonomous driving, and related topics as invited speakers at WAM-AD. Please submit your information via the Call for Speakers form.

Call for Reviewers

We welcome volunteers to join our program committee and help review workshop submissions. If you are interested, please sign up through the Call for Reviewers form.