WorldGen-1 simultaneously generates consistent sensor data across vision, perception (including semantic segmentation), and Lidar (bird’s-eye view and front view), along with an ego-vehicle path that accurately replicates real-world conditions.
WorldGen-1 enhances existing camera-only videos by extrapolating them to other modalities, including semantic segmentation, Lidar front view, and Lidar Bird’s-eye view. This enriches your datasets and reduces the need for costly data collection.
Our AI model predicts the behaviors of pedestrians, vehicles, and the ego-vehicle in multiple future scenarios, performing intent and path prediction in simulated and real environments.
WorldGen-1 creates scenarios complete with simulated Lidar output, segmentation masks, ego-vehicle paths, providing development teams with high-quality 3D labeled data for large-scale training and validation.
Explore Helm.ai’s modular AI software, fine-tunable DNN foundation models, and AI-based development and validation tools.
