Call for Papers

We invite paper submissions that present novel work, including initial ideas, methodological designs, and summaries of relevant past research on autonomous driving. We also welcome position papers and extended abstracts where participants can discuss future applications, especially identifying and avoiding out-of-label hazards in autonomous driving. In particular, we encourage submissions addressing current limitations in detecting, recognizing, and predicting hazards to inspire the new algorithms and systems inspired by areas such as Anomaly Detection, Open-Set Recognition, Open Vocabulary, and Domain Adaptation.

Researchers are also invited to submit short abstracts or paragraphs explaining their research plans, especially if they are still exploring how to approach both the computer vision and psychological aspects of avoiding hazards. We welcome contributions that outline research directions and challenges to foster discussions and collaborations that can push the boundaries of autonomous driving safety.

Submission guidelines

Please use the WACV '25 main conference template and author guidelines for all submissions.

• Option 1. Full papers: up to 8 pages excluding references (e.g., for novel work or summary of past work)

• Option 2. Extended abstracts and position papers: up to 4 pages, excluding references.

Papers should be submitted using the following CMT link.

Note: At 4 pages, submissions do not conflict with the CVPR dual submission policy. 

Important Dates:

• Workshop paper submission deadline: December 27th, 2024, 11:59 am (PST)

• Workshop Reviews deadline: January 6th, 2025 (PST)

• Workshop paper acceptance notification: January 8th, 2025 (PST)

• Workshop paper camera ready: January 10th, 2025 (PST)

List of topics: 

List of topics include but are not limited to:

• Detecting, recognizing, predicting, and avoiding out-of-label hazards.

• Detecting, recognizing, predicting activity understanding in autonomous driving

• Handling low-resolution hazards.

• New datasets and metrics for autonomous driving.

• Vision systems for autonomous driving.

• Vision-language models for autonomous driving.

• HRI: Human Factors in Autonomous Driving.

• Explainable AI in autonomous driving.

We can provide a few registrations for accepted papers in workshops and Kaggle challenge performance

based on financial need.