1 citations · 1 across the 9 of their papers we have counts for
10 papers
Learning Vision-Language-Action World Models for Autonomous Driving
Guoqing Wang, Pin Tang, Xiangxuan Ren +3
Vision-Language-Action (VLA) models have recently achieved notable progress in end-to-end autonomous driving by integrating perception, reasoning, and control within a unified mult…
Spatial4D-Bench: A Versatile 4D Spatial Intelligence Benchmark
Pan Wang, Yang Liu, Guile Wu +23
4D spatial intelligence involves perceiving and processing how objects move or change over time. Humans naturally possess 4D spatial intelligence, supporting a broad spectrum of sp…
GenieDrive: Towards Physics-Aware Driving World Model with 4D Occupancy Guided Video Generation
Zhenya Yang, Zhe Liu, Yuxiang Lu +6
Physics-aware driving world model is essential for drive planning, out-of-distribution data synthesis, and closed-loop evaluation. However, existing methods often rely on a single…
TurboVSR: Fantastic Video Upscalers and Where to Find Them
Zhongdao Wang, Guodongfang Zhao, Jingjing Ren +3
Diffusion-based generative models have demonstrated exceptional promise in the video super-resolution (VSR) task, achieving a substantial advancement in detail generation relative…
Efficient 3D Perception on Multi-Sweep Point Cloud with Gumbel Spatial Pruning
Tianyu Sun, Jianhao Li, Xueqian Zhang +3
This paper studies point cloud perception within outdoor environments. Existing methods face limitations in recognizing objects located at a distance or occluded, due to the sparse…
ReliOcc: Towards Reliable Semantic Occupancy Prediction via Uncertainty Learning
Song Wang, Zhongdao Wang, Jiawei Yu +4
Vision-centric semantic occupancy prediction plays a crucial role in autonomous driving, which requires accurate and reliable predictions from low-cost sensors. Although having not…
VEON: Vocabulary-Enhanced Occupancy Prediction
Jilai Zheng, Pin Tang, Zhongdao Wang +4
Perceiving the world as 3D occupancy supports embodied agents to avoid collision with any types of obstacle. While open-vocabulary image understanding has prospered recently, how t…
Segment, Lift and Fit: Automatic 3D Shape Labeling from 2D Prompts
Jianhao Li, Tianyu Sun, Zhongdao Wang +7
This paper proposes an algorithm for automatically labeling 3D objects from 2D point or box prompts, especially focusing on applications in autonomous driving. Unlike previous arts…
OccGen: Generative Multi-modal 3D Occupancy Prediction for Autonomous Driving
Guoqing Wang, Zhongdao Wang, Pin Tang +4
Existing solutions for 3D semantic occupancy prediction typically treat the task as a one-shot 3D voxel-wise segmentation perception problem. These discriminative methods focus on…
SparseOcc: Rethinking Sparse Latent Representation for Vision-Based Semantic Occupancy Prediction
Pin Tang, Zhongdao Wang, Guoqing Wang +4
Vision-based perception for autonomous driving requires an explicit modeling of a 3D space, where 2D latent representations are mapped and subsequent 3D operators are applied. Howe…