UniScene: Multi-Camera Unified Pre-training via 3D Scene Reconstruction for Autonomous Driving

Understand

Multi-camera 3D perception has emerged as a prominent research field in autonomous driving, offering a viable and cost-effective alternative to LiDAR-based solutions.

• The existing multi-camera algorithms primarily rely on monocular 2D pre-training.
• However, the monocular 2D pre-training overlooks the spatial and temporal correlations among the multi-camera system.
• To address this limitation, we propose the first multi-camera unified pre-training framework, called UniScene, which involves initially reconstructing the 3D scene as the foundational stage and subsequently fine-tuning the model on downstream tasks.