6 papers
X-Cache: Cross-Chunk Block Caching for Few-Step Autoregressive World Models Inference
Yixiao Zeng, Jianlei Zheng, Chaoda Zheng +10
Real-time world simulation is becoming a key infrastructure for scalable evaluation and online reinforcement learning of autonomous driving systems. Recent driving world models bui…
X-World: Controllable Ego-Centric Multi-Camera World Models for Scalable End-to-End Driving
Chaoda Zheng, Sean Li, Jinhao Deng +9
Scalable and reliable evaluation is increasingly critical in the end-to-end era of autonomous driving, where vision--language--action (VLA) policies directly map raw sensor streams…
FutureX: Enhance End-to-End Autonomous Driving via Latent Chain-of-Thought World Model
Hongbin Lin, Yiming Yang, Yifan Zhang +10
In autonomous driving, end-to-end planners learn scene representations from raw sensor data and utilize them to generate a motion plan or control actions. However, exclusive relian…
DriveFlow: Rectified Flow Adaptation for Robust 3D Object Detection in Autonomous Driving
Hongbin Lin, Yiming Yang, Chaoda Zheng +7
In autonomous driving, vision-centric 3D object detection recognizes and localizes 3D objects from RGB images. However, due to high annotation costs and diverse outdoor scenes, tra…
PiSA: A Self-Augmented Data Engine and Training Strategy for 3D Understanding with Large Models
Zilu Guo, Hongbin Lin, Zhihao Yuan +6
3D Multimodal Large Language Models (MLLMs) have recently made substantial advancements. However, their potential remains untapped, primarily due to the limited quantity and subopt…
Towards Flexible 3D Perception: Object-Centric Occupancy Completion Augments 3D Object Detection
Chaoda Zheng, Feng Wang, Naiyan Wang +2
While 3D object bounding box (bbox) representation has been widely used in autonomous driving perception, it lacks the ability to capture the precise details of an object's intrins…