Semi-Supervised Vision-Centric 3D Occupancy World Model for Autonomous Driving

Xiang Li, Pengfei Li, Yupeng Zheng, Wei Sun, Yan Wang, Yilun Chen

International Conference on Learning Representations (ICLR) 2025

Our semi-supervised 3D occupancy world model, featuring 2D rendering supervision and an end-to-end architecture, can forecast future occupancy straightly from image inputs while taking advantage of 2D labels.

[OpenReview] [Paper] [Code]

MonoOcc: Digging into Monocular Semantic Occupancy Prediction

Yupeng Zheng*, Xiang Li*, Pengfei Li, Yuhang Zheng, Bu Jin, Chengliang Zhong, Xiaoxiao Long, Hao Zhao, Qichao Zhang(* equal contribution)

International Conference on Robotics and Automation (ICRA) 2024

By proposing a distillation module to transfer temporal information and richer knowledge to the monocular branch from a privileged branch, we increase the performance of the framework especially on small and long-tailed objects, while striking a balance between performance and efficiency.

[Paper] [Code]