The CVPR 2025 Workshop on Autonomous Driving (WAD) brings together leading researchers and engineers from academia and industry to discuss the latest advances in autonomous driving. Now in its 8th year, the workshop has been continuously evolving with this rapidly changing field and now covers all areas of autonomy, including perception, behavior prediction and motion planning. In this full-day workshop, our keynote speakers will provide insights into the ongoing commercialization of autonomous vehicles, as well as progress in related fundamental research areas. Furthermore, we will host a series of technical benchmark challenges to help quantify recent advances in the field, and invite authors of accepted workshop papers to present their work.
- [Mar 18] The workshop will take place on Wednesday, June 11.
- [Mar 17] Our paper track is now closed. Thanks to everyone submitting their work!
- [Feb 24] We are pleased to also host the Nexar Dashcam Crash Prediction Challenge this year.
- [Feb 23] We released our call for papers.
- [Dec 20] The workshop got accepted. More updates to follow soon.
The workshop will host a variety of challenges to promote research in computer vision, behavor prediction and planning for autonomous driving. Our partners Waymo, Argoverse and Nexar have prepared large-scale benchmark datasets with high-quality ground truth annotations. We invite researchers around the world to tackle a range of challenging autonomous driving tasks.
Waymo Open Dataset Challenges
The 6th annual edition of the Waymo Open Dataset Challenges will be focused on the following topics:
- Scenario Generation
- Camera-based End-to-end Planning
- Interaction Prediction
- Sim Agents
More details will be announced soon. Refer to the challenge website for the latest updates.
Nexar Dashcam Crash Prediction Challenge
Autonomous vehicles and advanced driver assistance systems (ADAS) rely on accurate accident prediction to enhance road safety. In this competition, you will analyze dashcam videos and develop models capable of predicting vehicle collisions before they occur. The challenge includes real-world scenarios, such as diverse weather conditions, occlusions, and unexpected road events. Your goal is to develop a model that accurately predicts vehicle collisions as early as possible in dashcam video sequences. The earlier and more accurately you can detect an impending accident, the better your score. Submit to the challenge here.
Argoverse Challenges
Details will be announced soon.
Important Dates
- Workshop paper submission deadline:
Friday, March 14th, 2025Sunday, March 16th, 2025 (23:59 PST) - Notification to authors: Monday, March 30th, 2025 (23:59 PST)
- Camera ready deadline: Sunday, April 6th, 2025 (23:59 PST)
Topics Covered
We invite submissions of original research contributions in machine perception, computer vision, prediction, planning and simulation related to autonomous vehicles, such as (but not limited to):
- Foundational models for autonomous driving.
- Vision language models (VLMs) and large language models (LLMs) for solving autonomous vehicle related tasks such as prediction or planning.
- Autonomous navigation and exploration based on camera, laser, radar or related measurements.
- Embodied AI for autonomous driving.
- Sensor fusion and multi-modal perception algorithms for scene understanding.
- Bird’s eye view methods for autonomous driving, such as BEV-based 3D detection, BEV segmentation, occupancy grids, HD-maps, and topological lane graphs.
- Vision-based driving assistance, driver monitoring and advanced interfaces.
- Sensor simulation, neural rendering / NeRFs, 3D Gaussian Splatting, generative models for 3D assets or driving environments.
- Diffusion models for prediction and planning.
- Mapless autonomous driving.
- Cooperative perception and planning based on vehicle-to-everything (V2X) / vehicle-to-vehicle communication.
- Transfer learning and domain adaptation in the autonomous vehicle domain.
- Simulation for autonomous driving.
- Online sensor calibration.
- SLAM and 3D reconstruction algorithms.
- Validation and interpretability of autonomous systems.
- Adversarial learning, adversarial attacks, robustness and handling of uncertainty in autonomous systems.
Presentation Guidelines
Submission Instruction
- We are following the CVPR paper format: https://cvpr.thecvf.com/Conferences/2025/AuthorGuidelines
- LaTeX/Word Templates can be found here: CVPR 2025 Paper Template
- We accept full-length (max 8 pages) submissions, excluding references.
- All the submissions will be peer-reviewed by at least two reviewers.
- Blind review: we adopt double-blind review for this workshop. Submitted papers and supplementary materials should not reveal any information about the author.
- Dual submission: We do not accept paper submissions that have been published or are under review for other conferences or workshops. Accepted papers are expected to be published at CVPR proceedings.
- In submitting a manuscript to WAD Workshop, the authors agree to the review process and agree to contribute with the reviewing process.
Submission Instruction
Acknowledgment
