NEW YORK, Feb. 10, 2025 -- Nexar, a leader in AI-powered mobility solutions, today announced the release of a groundbreaking open dataset and the launch of Nexar Dashcam Crash Prediction Challenge, a global competition on Kaggle, aimed at advancing collision prediction capabilities using computer vision. This initiative underscores Nexar's commitment to fostering innovation and positioning itself at the forefront of AI-driven road safety advancements while promoting its technology to the global AI and autonomous vehicle (AV) communities.
"This project underscores our commitment to innovation," said Luc Vincent, Chief R&D Officer, Nexar. "We invite the AI community to engage with our data, explore its possibilities, and showcase the next level of predictive modeling in collision detection."
The Open Dataset: A New Frontier in Predictive Modeling
Nexar's Open Dataset includes anonymized video samples from real-world driving scenarios, designed to challenge participants and drive advancements in predictive modeling. The dataset is expected to contain 1500 videos with roughly half being near or actual collisions and the other half being normal driving videos.
The data will be hosted on Hugging Face, a leading platform for sharing machine learning datasets and models. Released under a permissive license (MIT), the dataset will be openly accessible for both academic research and industry applications. To ensure privacy, all faces, dashboards, and other sensitive information are anonymized, with additional measures taken to exclude videos captured near residential areas. Nexar's efforts in creating and sharing this dataset demonstrate its dedication to fostering collaboration and engagement with academic institutions and industry leaders.
"By choosing a permissive license, we aim to maximize the dataset's impact," said Vincent. "Whether in academia or industry, anyone can engage with our data, recognize its potential, and explore future opportunities to collaborate with Nexar."
Advancing Collision Prediction through Global Collaboration
In conjunction with its Open Dataset release, Nexar is launching a global Nexar Dashcam Crash Prediction Challenge aimed at fostering innovation in collision prediction. The competition welcomes researchers, students, and professionals globally to leverage Nexar's dataset and contribute to advancements in road safety technology. Nexar hopes to showcase the capabilities of AI-driven insights in advancing road safety through the competition's results.
Participants will compete to build models that predict whether a collision will occur in upcoming video frames. Participants will analyze video sequences to predict collisions, focusing on early and accurate detection. Submissions will be ranked based on accuracy and the timeliness of collision detection.
The competition is now open and will conclude on May 4, 2025.
Following the competition, Nexar plans to analyze the results and present key findings at CVPR 2025, the world's leading computer vision conference. Additionally, Nexar aims to publish two academic papers detailing the dataset's creation and insights gained from the competition.
The grand prize will be an exciting VIP trip to visit Nexar's HQ in Porto, Portugal, where the team will be invited to present their work to the Nexar engineering and research teams and meeting company leaders.
For more information about Nexar's open dataset, visit https://huggingface.co/datasets/nexar-ai/nexar_collision_prediction and to join the Nexar Dashcam Crash Prediction Challenge, visit https://www.kaggle.com/competitions/nexar-collision-prediction.
About Nexar
Nexar turns cars into vision sensors to understand the world. Its platform powers vision-connected services and apps at scale, making new vision-based applications for better driving powered by a crowd-sourced vision feed. Using anonymous, aggregated data captured from this network, Nexar has developed a portfolio of vision-based data services for the autonomous vehicle industry and public and private sector partners to make roadways safer and more efficient. More information at https://www.nexar-ai.com/.
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